tailieunhanh - ROBOTICS Handbook of Computer Vision Algorithms in Image Algebra Part 1

Tham khảo tài liệu 'robotics handbook of computer vision algorithms in image algebra part 1', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | EARTHWEB HOME SUBSCRIBE FAQ SITEMAP ft KEY Vi ORD SEARCH GOỈ SM IT Need IT. Find IT. Know IT. Search Tips Handbook of Computer Vision Algorithms in Image Algebra by Gerhard X. Ritter Joseph N. Wilson CRC Press CRC Press LLC ISBN 0849326362 Pub Date 05 01 96 Search this book invariant GO Advanced Search Preface Acknowledgments Chapter 1 Image Algebra . Introduction . Point Sets . Value Sets . Images . Templates . Recursive Templates . Neighborhoods . The p-Product . References Chapter 2 Image Enhancement Techniques . Introduction . Averaging of Multiple Images . Local Averaging . Variable Local Averaging . Iterative Conditional Local Averaging . Max-Min Sharpening Transform . Smoothing Binary Images by Association . Median Filter . Unsharp Masking . Local Area Contrast Enhancement . Histogram Equalization . Histogram Modification . Lowpass Filtering . Highpass Filtering . References Chapter 3 Edge Detection and Boundary Finding Techniques . Introduction . Binary Image Boundaries . Edge Enhancement by Discrete Differencing . Roberts Edge Detector . Prewitt Edge Detector . Sobel Edge Detector . Wallis Logarithmic Edge Detection . Frei-Chen Edge and Line Detection . Kirsch Edge Detector . Directional Edge Detection . Product of the Difference of Averages . Crack Edge Detection . Local Edge Detection in Three-Dimensional Images . Hierarchical Edge Detection . Edge Detection Using K-Forms . Hueckel Edge Operator . Divide-and-Conquer Boundary Detection . Edge Following as Dynamic Programming . References Chapter 4 Thresholding Techniques . Introduction . Global Thresholding . Semithresholding . Multilevel Thresholding . Variable Thresholding . Threshold Selection Using Mean and Standard Deviation . Threshold Selection by Maximizing Between-Class Variance . Threshold Selection Using a Simple .