Modern Algorithms for Image Processing [electronic resource] : Computer Imagery by Example Using C# /
Kovalevsky, Vladimir.author.
Utilize modern methods for digital image processing and take advantage of the many time-saving templates provided for all of the projects included in this book. Modern Algorithms for Image Processing approaches the topic of image processing through teaching by example. Throughout the book, you will create projects that resolve typical problems that you might encounter in the world of digital image processing. Some example projects teach you how to address the quality of images, such as reducing random errors or noise. Other methods will teach you how to correct inhomogeneous illumination, not by means of subtracting the mean illumination, but through division, which is a far more efficient method. Additional projects cover contrasting, edge detection, and edge detection in color images, which are important concepts to understand for image analysis. This book does not prove or disprove theorems, but instead details suggested methods to help you learn valuable concepts and how to customize your own image processing projects. What You'll Learn: Know the pros and cons of enlisting a particular method Use new methods for image compression and recognizing circles in photos Utilize a method for straightening photos of paintings taken at an oblique angle, a critical concept to understand when using flash at a right angle Understand the problem statement of polygonal approximation of boundaries or edges and its solution Access complete source code examples of all projects on GitHub The book is for C# developers who work with digital image processing or are interested in informatics. The reader should have programming experience and access to an integrated development environment (IDE), ideally .NET. Vladimir A. Kovalevsky holds a diploma in physics, a PhD in technical sciences, and a PhD in computer science. He has been a researcher, professor, and visiting professor at many esteemed universities worldwide, including the Central Institute of Cybernetics of the Academy of Sciences, University of Applied Sciences, and the Manukau Institute of Technology. Dr. Kovalevsky has been a plenary speaker at many conferences and his research interests include digital geometry, digital topology, computer vision, image processing, and pattern recognition. He has published four monographs and more than 180 journal and conference papers.
Includes bibliographical references and index.
Part I: Image Processing -- Chapter 1: Introduction -- Chapter 2: Noise Reduction -- Chapter 3: Contrast Enhancement -- Chapter 4: Shading Correction with Thresholding -- Chapter 5: Project "WFshadBinImpulse" -- Part II: Image Analysis -- Chapter 6: Edge Detection -- Chapter 7: A New Method of Edge Detection -- Chapter 8: A New Method of image Compression -- Chapter 9: Image Segmentation and Connected Components -- Chapter 10: Straightening Photos of Paintings -- Chapter 11: Polygonal Approximation of Region Boundaries and Edges -- Chapter 12: Recognition and Measurement of Circular Objects -- Chapter 13: Recognition of Bicycles in Traffic -- Appendix A: References.
Utilize modern methods for digital image processing and take advantage of the many time-saving templates provided for all of the projects included in this book. Modern Algorithms for Image Processing approaches the topic of image processing through teaching by example. Throughout the book, you will create projects that resolve typical problems that you might encounter in the world of digital image processing. Some example projects teach you how to address the quality of images, such as reducing random errors or noise. Other methods will teach you how to correct inhomogeneous illumination, not by means of subtracting the mean illumination, but through division, which is a far more efficient method. Additional projects cover contrasting, edge detection, and edge detection in color images, which are important concepts to understand for image analysis. This book does not prove or disprove theorems, but instead details suggested methods to help you learn valuable concepts and how to customize your own image processing projects. What You'll Learn: Know the pros and cons of enlisting a particular method Use new methods for image compression and recognizing circles in photos Utilize a method for straightening photos of paintings taken at an oblique angle, a critical concept to understand when using flash at a right angle Understand the problem statement of polygonal approximation of boundaries or edges and its solution Access complete source code examples of all projects on GitHub The book is for C# developers who work with digital image processing or are interested in informatics. The reader should have programming experience and access to an integrated development environment (IDE), ideally .NET. Vladimir A. Kovalevsky holds a diploma in physics, a PhD in technical sciences, and a PhD in computer science. He has been a researcher, professor, and visiting professor at many esteemed universities worldwide, including the Central Institute of Cybernetics of the Academy of Sciences, University of Applied Sciences, and the Manukau Institute of Technology. Dr. Kovalevsky has been a plenary speaker at many conferences and his research interests include digital geometry, digital topology, computer vision, image processing, and pattern recognition. He has published four monographs and more than 180 journal and conference papers.
Microsoft software.
Microsoft .NET Framework.
Optical data processing.
Microsoft and .NET.
Image Processing and Computer Vision.