LEADER 04982nam 22005775 450 001 9910338006003321 005 20200701022405.0 010 $a9781484242377 010 $a1484242378 024 7 $a10.1007/978-1-4842-4237-7 035 $a(CKB)4100000007204884 035 $a(MiAaPQ)EBC5613402 035 $a(DE-He213)978-1-4842-4237-7 035 $a(CaSebORM)9781484242377 035 $a(PPN)232967717 035 $a(OCoLC)1085513943 035 $a(OCoLC)on1085513943 035 $a(EXLCZ)994100000007204884 100 $a20181210d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModern Algorithms for Image Processing $eComputer Imagery by Example Using C# /$fby Vladimir Kovalevsky 205 $a1st ed. 2019. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2019. 215 $a1 online resource (279 pages) 311 08$a9781484242360 311 08$a148424236X 320 $aIncludes bibliographical references and index. 327 $aPart 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. 330 $aUtilize 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. 606 $aMicrosoft software 606 $aMicrosoft .NET Framework 606 $aOptical data processing 606 $aMicrosoft and .NET$3https://scigraph.springernature.com/ontologies/product-market-codes/I29030 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 615 0$aMicrosoft software. 615 0$aMicrosoft .NET Framework. 615 0$aOptical data processing. 615 14$aMicrosoft and .NET. 615 24$aImage Processing and Computer Vision. 676 $a621.367 700 $aKovalevsky$b Vladimir$4aut$4http://id.loc.gov/vocabulary/relators/aut$01060062 801 0$bUMI 801 1$bUMI 906 $aBOOK 912 $a9910338006003321 996 $aModern Algorithms for Image Processing$92510912 997 $aUNINA