Download or read book Visual Media Processing Using Matlab Beginner s Guide written by George Siogkas and published by Packt Publishing Ltd. This book was released on 2013-09-24 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in a friendly, Beginner's Guide format, showing the user how to use the digital media aspects of Matlab (image, video, sound) in a practical, tutorial-based style.This is great for novice programmers in any language who would like to use Matlab as a tool for their image and video processing needs, and also comes in handy for photographers or video editors with even less programming experience wanting to find an all-in-one tool for their tasks.

Download or read book Getting Started with Simulink written by Luca Zamboni and published by Packt Publishing Ltd. This book was released on 2013-10-25 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical and easy-to-understand learning tutorial is one big exciting exercise for students and engineers that are always short on their schedules and want to regain some lost time with the help of Simulink.This book is aimed at students and engineers who need a quick start with Simulink. Though it's not required in order to understand how Simulink works, knowledge of physics will help the reader to understand the exercises described.

Download or read book Image Processing Recipes in MATLAB written by Oge Marques and published by CRC Press. This book was released on 2024-05-16 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leveraging the latest developments in MATLAB and its image processing toolbox, this 'cookbook' is a collection of 30 practical recipes for image processing, ranging from foundational techniques to recently published algorithms. Presented in a clear and meaningful sequence, these recipes are prepared with the reader in mind, allowing one to focus on particular topics or read as a whole from cover to cover. Key Features: A practical, user-friendly guide that equips researchers and practitioners with the tools to implement efficient image processing workflows in MATLAB. Each recipe is presented through clear, step-by-step instructions and rich visual examples. Each recipe contains its own source code, explanations, and figures, making the book an excellent standalone resource for quick reference. Strategically structured to aid sequential learning, yet with self-contained chapters for those seeking solutions to specific image processing challenges. The book serves as a concise and readable practical reference to deploy image processing pipelines in MATLAB quickly and efficiently. With its accessible and practical approach, the book is a valuable guide for those who navigate this evolving area, including researchers, students, developers, and practitioners in the fields of image processing, computer vision, and image analysis.

Download or read book The Absolute Beginner s Guide to Learn Database Programming Using Python GUI with PostgreSQL and SQL Server written by Vivian Siahaan and published by SPARTA PUBLISHING. This book was released on 2020-01-16 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide to Python as one of the fastest-growing computer languages including Web and Internet applications. This clear and concise introduction to the Python language is aimed at readers who are already familiar with programming in at least one language. This hands-on book introduces the essential topic of coding and the Python computer language to beginners and pogrammers of all ages. This book explains relational theory in practice, and demonstrates through two projects how you can apply it to your use of PostgreSQL and SQL Server databases. This book covers the important requirements of teaching databases with a practical and progressive perspective. This book offers the straightforward, practical answers you need to help you do your job. This hands-on tutorial/reference/guide to PostgreSQL and SQL Server is not only perfect for students and beginners, but it also works for experienced developers who aren't getting the most from both databases. In designing a GUI and as an IDE, you will make use Qt Designer. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In chapter three, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In chapter four, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In chapter five, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter six, you will get introduction of postgresql. And then, you will learn querying data from the postgresql using Python including establishing a database connection, creating a statement object, executing the query, processing the resultset object, querying data using a statement that returns multiple rows, querying data using a statement that has parameters, inserting data into a table using Python, updating data in postgresql database using Python, calling postgresql stored function using Python, deleting data from a postgresql table using Python, and postgresql Python transaction. In chapter seven, you will create dan configure PotgreSQL database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter eight, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have a VARCHAR data type (200). You will also create GUI to display, edit, insert, and delete for this table. In chapter nine, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In chapter ten, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables as well.

Download or read book The Absolute Beginner s Guide to Learn Database Programming Using Python GUI with MariaDB and SQL Server written by Vivian Siahaan and published by SPARTA PUBLISHING. This book was released on 2020-01-16 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to introduce programmers to programming and computational thinking through the lens of exploring database. This book offers Python programmers one place to look when they need help guiding to Python as one of the fastest-growing computer languages including Web and Internet applications. This clear and concise introduction to the Python language is aimed at readers who are already familiar with programming in at least one language. This hands-on book introduces the essential topic of coding and the Python computer language to beginners and pogrammers of all ages. This book explains relational theory in practice, and demonstrates through two projects how you can apply it to your use of MariaDB and SQL Server databases. This book covers the important requirements of teaching databases with a practical and progressive perspective. This book offers the straightforward, practical answers you need to help you do your job. This hands-on tutorial/reference/guide to MariaDB and SQL Server is not only perfect for students and beginners, but it also works for experienced developers who aren't getting the most from both databases. In designing a GUI and as an IDE, you will make use Qt Designer. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In chapter three, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In chapter four, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In chapter five, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter six, you will create dan configure database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter seven, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have a VARCHAR data type (200). You will also create GUI to display, edit, insert, and delete for this table. In chapter eight, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In chapter nine, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables as well.

Download or read book The Beginner s Guide to Learn Python GUI with PostgreSQL and SQLite written by Vivian Siahaan and published by SPARTA PUBLISHING. This book was released on 2020-01-15 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains relational theory in practice, and demonstrates through two projects how you can apply it to your use of PostgreSQL and SQLite databases. This book covers the important requirements of teaching databases with a practical and progressive perspective. This book offers the straightforward, practical answers you need to help you do your job. This hands-on tutorial/reference/guide to PostgreSQL and SQLite is not only perfect for students and beginners, but it also works for experienced developers who aren't getting the most from both databases. In designing a GUI and as an IDE, you will make use Qt Designer. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In chapter three, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In chapter four, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In chapter five, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter six and chapter seven, you will get introduction of postgresql. And then, you will learn querying data from the postgresql using Python including establishing a database connection, creating a statement object, executing the query, processing the resultset object, querying data using a statement that returns multiple rows, querying data using a statement that has parameters, inserting data into a table using Python, updating data in postgresql database using Python, calling postgresql stored function using Python, deleting data from a postgresql table using Python, and postgresql Python transaction. In chapter eight, you will create dan configure PotgreSQL database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter nine, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have a VARCHAR data type (200). You will also create GUI to display, edit, insert, and delete for this table. In chapter ten, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In chapter eleven, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables as well.

Download or read book The Absolute Beginner s Guide to Learn Python GUI with MySQL and SQL Server Databases written by Vivian Siahaan and published by SPARTA PUBLISHING. This book was released on 2020-01-16 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This hands-on book introduces the essential topic of coding and the Python computer language to beginners and pogrammers of all ages. This book explains relational theory in practice, and demonstrates through two projects how you can apply it to your use of MySQL and SQL Server databases. This book covers the important requirements of teaching databases with a practical and progressive perspective. This book offers the straightforward, practical answers you need to help you do your job. This hands-on tutorial/reference/guide to MySQL and SQL Server is not only perfect for students and beginners, but it also works for experienced developers who aren't getting the most from both databases. In designing a GUI and as an IDE, you will make use Qt Designer. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In chapter three, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In chapter four, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In chapter five, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter six, you will create dan configure database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter seven, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have VARBINARY(MAX) data type. You will also create GUI to display, edit, insert, and delete for this table. In chapter eight, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In the last chapter, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables.

Download or read book MATLAB for Machine Learning written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2017-08-28 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extract patterns and knowledge from your data in easy way using MATLAB About This Book Get your first steps into machine learning with the help of this easy-to-follow guide Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn Learn the introductory concepts of machine learning. Discover different ways to transform data using SAS XPORT, import and export tools, Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Download or read book A Guide to MATLAB written by Brian R. Hunt and published by Cambridge University Press. This book was released on 2001-08-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a short, focused introduction to MATLAB and should be useful to both beginning and experienced users.

Download or read book Digital Media written by Rimon Elias and published by Springer Science & Business Media. This book was released on 2014-03-27 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on the computer graphics required to create digital media this book discusses the concepts and provides hundreds of solved examples and unsolved problems for practice. Pseudo codes are included where appropriate but these coding examples do not rely on specific languages. The aim is to get readers to understand the ideas and how concepts and algorithms work, through practicing numeric examples. Topics covered include: 2D Graphics 3D Solid Modelling Mapping Techniques Transformations in 2D and 3D Space Illuminations, Lighting and Shading Ideal as an upper level undergraduate text, Digital Media – A Problem-solving Approach for Computer Graphic, approaches the field at a conceptual level thus no programming experience is required, just a basic knowledge of mathematics and linear algebra.

Download or read book VISUAL C NET A Step By Step Project Based Guide to Develop Desktop Applications written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2020-11-23 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: In chapter one, you will learn to know the properties and events of each control in a Windows Visual C# application. You need to learn and know in order to be more familiar when applying them to some applications in this book. In chapter two, you will build a project so that children can practice basic skills in addition, subtraction, multiplication, and division operations. This Math Game project can be used to choose the types of questions and what factors you want to use. This project has three timing options. Random math problems using values ​​from 0 to 9 will be presented. Timing options are provided to measure accuracy and speed. There are many controls used. Two label controls are used for title information, two for displaying scores. There is a wide label in the middle of the form to display math questions. And, long skinny label is used as separator. Two button controls are used to start and stop question and one button to exit the project. There are three group control boxes. The first group box holds four check box controls that are used to select the type of questions. The second group box holds eleven radio buttons that are used to select values ​​that are used as factors in calculations. The third group box contains three radio button controls for timing options. A scroll bar control rod is used to change the time. In chapter three, you will build Bank Code game. The storage box is locked and can only be opened if you enter the correct digit combination. Combinations can be 2 to 4 non-repetitive digits (range of digits from 1 to 9). After a guess is given, you will be notified of how many digits are right and how many digits are in the right position. Based on this information, you will give another guess. You continue to guess until you get the right combination or until you stop the game. On the left side of the form is a large picture box control. On the right side, two group box controls and two button controls are placed. In the picture box, a control panel is placed. In the panel, there are four label controls (set the AutoSize property to False) and nine button controls. In the first group box control, place three radio buttons. In the second group box control, a text box control is placed. The picture box contains an image of bank and a panel. The label controls in the panel are used to display the combinations entered (the BorderStyle property set to FixedSingle to display the label size). The nine buttons on the panel are used to enter combinations. Radio buttons are used to set options. The buttons (one to start and stop the game and another to exit the project) are used to control game operations. The text box displays the results of the combinations entered. In chapter four, you will build Horse Racing game. This is a simple game. Up to 10 horses will race to the finish line. You guessed two horses that you thought could win the race. By clicking on the Start button, the race will start. All horses will race speed to get to the finish line. Labels are used to display instructions and number of horses in a race. Four button controls are used: two buttons to change number of horses, one button to start the game, and one other button to stop the game. The picture box control is used to load the horse image. A timer control is used to update the horse's movement during the race. In chapter five, you will build Catching Ball game. The bird flew and dropped ball from the sky. Users are challenged to position man under the fallen ball to catch it. Labels are used for instructions and to display game information (remaining time, number of balls captured, and game difficulty level). Two buttons are used to change the game difficulty level, one button to start the game, and another button to stop the game. Picture box controls hold images for man, bird, and ball. In chapter six, you will build Smart Tic Tac Toe game. That said, this is the first game ever programmed on a computer and one that had been programmed by Bill Gates himself when he was a teenager while attending Lakeside School in Seattle. The aim of this game is to win the game on a 3 x 3 grid with the victory of three identical symbols (X or O) on horizontal, diagonal, or vertical lines. The players will play alternately. In this game given two game options: player 1 against player 2 or human player against computer. A smart but simple strategy will be developed for computer logic to be a formidable opponent for humans. In chapter seven, you will build Fighting Plane program. This program can be played by two human players or human player versus computer. The controls of the player are done via the keyboard. Player 1 presses A key to move up, Z key to move down, and S key to throw rudal. When you choose Two players from the Options button, this game can be played by two human players. Player 1 presses the same keys, while player 2 presses key K to move up, M to move down, and key J to throw rudal. All label controls are used for titles and provide scoring and game information. The large panel (Panel1) is the playing field. Three button controls are used to start / stop a program, set options, and exit the program. One timer control is used to control game animation and another is used to represent the computer's decision process. The second control panel (Panel2) is used to select game options. One group box contains radio buttons which are used to select number of players. A group box contains radio buttons to select the level of difficulty of the game, when playing against a computer. A small button is used to close the options panel. The default properties are set for one-player games with the easiest game difficulty.

Download or read book Fundamentals of Image Audio and Video Processing Using MATLAB and Fundamentals of Graphics Using MATLAB written by Ranjan Parekh and published by CRC Press. This book was released on 2021-07-01 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: This discounted two-book set contains BOTH: Fundamentals of Image, Audio, and Video Processing Using MATLAB® introduces the concepts and principles of media processing and its applications in pattern recognition by adopting a hands-on approach using program implementations. The book covers the tools and techniques for reading, modifying, and writing image, audio, and video files using the data analysis and visualization tool MATLAB®. This is a perfect companion for graduate and post-graduate students studying courses on image processing, speech and language processing, signal processing, video object detection and tracking, and related multimedia technologies, with a focus on practical implementations using programming constructs and skill developments. It will also appeal to researchers in the field of pattern recognition, computer vision and content-based retrieval, and for students of MATLAB® courses dealing with media processing, statistical analysis, and data visualization. Fundamentals of Graphics Using MATLAB® introduces fundamental concepts and principles of 2D and 3D graphics and is written for undergraduate and postgraduate students of computer science, graphics, multimedia, and data science. It demonstrates the use of MATLAB® programming for solving problems related to graphics and discusses a variety of visualization tools to generate graphs and plots. The book covers important concepts like transformation, projection, surface generation, parametric representation, curve fitting, interpolation, vector representation, and texture mapping, all of which can be used in a wide variety of educational and research fields. Theoretical concepts are illustrated using a large number of practical examples and programming codes, which can be used to visualize and verify the results.

Download or read book Practical Image and Video Processing Using MATLAB written by Oge Marques and published by John Wiley & Sons. This book was released on 2011-08-04 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: UP-TO-DATE, TECHNICALLY ACCURATE COVERAGE OF ESSENTIAL TOPICS IN IMAGE AND VIDEO PROCESSING This is the first book to combine image and video processing with a practical MATLAB®-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation. The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB® and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation. Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB®. Extra features of this book include: More than 30 MATLAB® tutorials, which consist of step-by-step guides toexploring image and video processing techniques using MATLAB® Chapters supported by figures, examples, illustrative problems, and exercises Useful websites and an extensive list of bibliographical references This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own.

Download or read book Guide to Signals and Patterns in Image Processing written by Apurba Das and published by Springer. This book was released on 2015-04-22 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text reviews the field of digital image processing from the different perspectives offered by the separate domains of signal processing and pattern recognition. The book describes a rich array of applications, representing the latest trends in industry and academic research. To inspire further interest in the field, a selection of worked-out numerical problems is also included in the text. The content is presented in an accessible manner, examining each topic in depth without assuming any prior knowledge from the reader, and providing additional background material in the appendices. Features: covers image enhancement techniques in the spatial domain, the frequency domain, and the wavelet domain; reviews compression methods and formats for encoding images; discusses morphology-based image processing; investigates the modeling of object recognition in the human visual system; provides supplementary material, including MATLAB and C++ code, and interactive GUI-based modules, at an associated website.

Download or read book Step By Step Database Programming with JDBC and PostgreSQL written by Vivian Siahaan and published by SPARTA Publishing. This book was released on 2019-04-08 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: PostgreSQL was designed to run on UNIX-like platforms. However, PostgreSQL was then also designed to be portable so that it could run on various platforms such as Mac OS X, Solaris, and Windows. PostgreSQL is free and open source software. Its source code is available under PostgreSQL license, a liberal open source license. You are free to use, modify and distribute PostgreSQL in any form. PostgreSQL requires very minimum maintained efforts because of its stability. Therefore, if you develop applications based on PostgreSQL, the total cost of ownership is low in comparison with other database management systems. In Chapter 2, you will learn querying data from the postgresql using jdbc including establishing a database connection, creating a statement object, executing the query, processing the resultset object, querying data using a statement that returns multiple rows, querying data using a statement that has parameters, inserting data into a table using jdbc, updating data in postgresql database using jdbc, calling postgresql stored function using jdbc, deleting data from a postgresql table using jdbc, and postgresql jdbc transaction. In Chapter 3, you will learn managing table structure and views including postgresql data types, postgresql create table, postgresql select into statement, postgresql create table as, using postgresql serial to create auto-increment column, identity column, alter table, drop table, truncate table, check constraint, not-null constraint, foreign key, primary key, unique constraint, managing postgresql views, creating updatable views, materialized views, creating updatable views using the with check option clause, and recursive view. In Chapter 4, you will learn statements, operators, and clauses including select, order by, select distinct, limit, fetch, in, between, postgresql like, is null, alias, joins, inner join, postgresql left join, self-join, full outer join, cross join, natural join, group by, having, intersect operator, except operator, grouping sets, cube, and rollup. In Chapter 5, you will learn postgresql trigger, aggregate, and string functions including creating the first trigger in postgresql, managing postgresql trigger, aggregate functions, avg function, max function, min function, sum function, postgresql concat function, ascii function, trim function, length function, substring function, regexp_matches function, regexp_replace function, replace function, to_number function, and to_char function.

Download or read book The Practical Guides on Deep Learning Using SCIKIT LEARN KERAS and TENSORFLOW with Python GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2023-06-17 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to implement deep learning on recognizing traffic signs using GTSRB dataset, detecting brain tumor using Brain Image MRI dataset, classifying gender, and recognizing facial expression using FER2013 dataset In Chapter 1, you will learn to create GUI applications to display image histogram. It is a graphical representation that displays the distribution of pixel intensities in an image. It provides information about the frequency of occurrence of each intensity level in the image. The histogram allows us to understand the overall brightness or contrast of the image and can reveal important characteristics such as dynamic range, exposure, and the presence of certain image features. In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, Pandas, NumPy and other libraries to perform prediction on handwritten digits using MNIST dataset. The MNIST dataset is a widely used dataset in machine learning and computer vision, particularly for image classification tasks. It consists of a collection of handwritten digits from zero to nine, where each digit is represented as a 28x28 grayscale image. The dataset was created by collecting handwriting samples from various individuals and then preprocessing them to standardize the format. Each image in the dataset represents a single digit and is labeled with the corresponding digit it represents. The labels range from 0 to 9, indicating the true value of the handwritten digit. In Chapter 3, you will learn how to perform recognizing traffic signs using GTSRB dataset from Kaggle. There are several different types of traffic signs like speed limits, no entry, traffic signals, turn left or right, children crossing, no passing of heavy vehicles, etc. Traffic signs classification is the process of identifying which class a traffic sign belongs to. In this Python project, you will build a deep neural network model that can classify traffic signs in image into different categories. With this model, you will be able to read and understand traffic signs which are a very important task for all autonomous vehicles. You will build a GUI application for this purpose. In Chapter 4, you will learn how to perform detecting brain tumor using Brain Image MRI dataset. Following are the steps taken in this chapter: Dataset Exploration: Explore the Brain Image MRI dataset from Kaggle. Describe the structure of the dataset, the different classes (tumor vs. non-tumor), and any preprocessing steps required; Data Preprocessing: Preprocess the dataset to prepare it for model training. This may include tasks such as resizing images, normalizing pixel values, splitting data into training and testing sets, and creating labels; Model Building: Use TensorFlow and Keras to build a deep learning model for brain tumor detection. Choose an appropriate architecture, such as a convolutional neural network (CNN), and configure the model layers; Model Training: Train the brain tumor detection model using the preprocessed dataset. Specify the loss function, optimizer, and evaluation metrics. Monitor the training process and visualize the training/validation accuracy and loss over epochs; Model Evaluation: Evaluate the trained model on the testing dataset. Calculate metrics such as accuracy, precision, recall, and F1 score to assess the model's performance; Prediction and Visualization: Use the trained model to make predictions on new MRI images. Visualize the predicted results alongside the ground truth labels to demonstrate the effectiveness of the model. Finally, you will build a GUI application for this purpose. In Chapter 5, you will learn how to perform classifying gender using dataset provided by Kaggle using MobileNetV2 and CNN models. Following are the steps taken in this chapter: Data Exploration: Load the dataset using Pandas, perform exploratory data analysis (EDA) to gain insights into the data, and visualize the distribution of gender classes; Data Preprocessing: Preprocess the dataset by performing necessary transformations, such as resizing images, converting labels to numerical format, and splitting the data into training, validation, and test sets; Model Building: Use TensorFlow and Keras to build a gender classification model. Define the architecture of the model, compile it with appropriate loss and optimization functions, and summarize the model's structure; Model Training: Train the model on the training set, monitor its performance on the validation set, and tune hyperparameters if necessary. Visualize the training history to analyze the model's learning progress; Model Evaluation: Evaluate the trained model's performance on the test set using various metrics such as accuracy, precision, recall, and F1 score. Generate a classification report and a confusion matrix to assess the model's performance in detail; Prediction and Visualization: Use the trained model to make gender predictions on new, unseen data. Visualize a few sample predictions along with the corresponding images. Finally, you will build a GUI application for this purpose. In Chapter 6, you will learn how to perform recognizing facial expression using FER2013 dataset using CNN model. The FER2013 dataset contains facial images categorized into seven different emotions: anger, disgust, fear, happiness, sadness, surprise, and neutral. To perform facial expression recognition using this dataset, you would typically follow these steps; Data Preprocessing: Load and preprocess the dataset. This may involve resizing the images, converting them to grayscale, and normalizing the pixel values; Data Split: Split the dataset into training, validation, and testing sets. The training set is used to train the model, the validation set is used to tune hyperparameters and evaluate the model's performance during training, and the testing set is used to assess the final model's accuracy; Model Building: Build a deep learning model using TensorFlow and Keras. This typically involves defining the architecture of the model, selecting appropriate layers (such as convolutional layers, pooling layers, and fully connected layers), and specifying the activation functions and loss functions; Model Training: Train the model using the training set. This involves feeding the training images through the model, calculating the loss, and updating the model's parameters using optimization techniques like backpropagation and gradient descent; Model Evaluation: Evaluate the trained model's performance using the validation set. This can include calculating metrics such as accuracy, precision, recall, and F1 score to assess how well the model is performing; Model Testing: Assess the model's accuracy and performance on the testing set, which contains unseen data. This step helps determine how well the model generalizes to new, unseen facial expressions; Prediction: Use the trained model to make predictions on new images or live video streams. This involves detecting faces in the images using OpenCV, extracting facial features, and feeding the processed images into the model for prediction. Then, you will also build a GUI application for this purpose.

Download or read book ZERO TO MASTERY THE COMPLETE GUIDE TO LEARNING SQLITE AND PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-08-17 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this project, we provide you with the SQLite version of The Oracle Database Sample Schemas that provides a common platform for examples in each release of the Oracle Database. The sample database is also a good database for practicing with SQL, especially SQLite. The detailed description of the database can be found on: http://luna-ext.di.fc.ul.pt/oracle11g/server.112/e10831/diagrams.htm#insertedID0. The four schemas are a set of interlinked schemas. This set of schemas provides a layered approach to complexity: A simple schema Human Resources (HR) is useful for introducing basic topics. An extension to this schema supports Oracle Internet Directory demos; A second schema, Order Entry (OE), is useful for dealing with matters of intermediate complexity. Many data types are available in this schema, including non-scalar data types; The Online Catalog (OC) subschema is a collection of object-relational database objects built inside the OE schema; The Product Media (PM) schema is dedicated to multimedia data types; The Sales History (SH) schema is designed to allow for demos with large amounts of data. An extension to this schema provides support for advanced analytic processing. The HR schema consists of seven tables: regions, countries, locations, departments, employees, jobs, and job_histories. This book only implements HR schema, since the other schemas will be implemented in the next books.