基本説明
A general textbook presents in a systematic way the modern signal processing concepts used in computer vision and image analysis. The topics include Hilbert spaces, Fourier transform, scale analysis, direction fields, structure tensor, motion tensor, Hough transform, grouping, and segmentation.
Full Description
Image analysis is a computational feat which humans show excellence in, in comp- ison with computers. Yet the list of applications that rely on automatic processing of images has been growing at a fast pace. Biometric authentication by face, ?ngerprint, and iris, online character recognition in cell phones as well as drug design tools are but a few of its benefactors appearing on the headlines. This is, of course, facilitated by the valuable output of the resarch community in the past 30 years. The pattern recognition and computer vision communities that study image analysis have large conferences, which regularly draw 1000 parti- pants. In a way this is not surprising, because much of the human-speci?c activities critically rely on intelligent use of vision. If routine parts of these activities can be automated, much is to be gained in comfort and sustainable development. The - search ?eld could equally be called visualintelligence because it concerns nearly all activities of awake humans. Humans use or rely on pictures or pictorial languages to represent, analyze, and develop abstract metaphors related to nearly every aspect of thinking and behaving, be it science, mathematics, philosopy, religion, music, or emotions. The present volume is an introductory textbook on signal analysis of visual c- putation for senior-level undergraduates or for graduate students in science and - gineering. My modest goal has been to present the frequently used techniques to analyze images in a common framework-directional image processing.
Contents
Human and Computer Vision.- Neuronal Pathways of Vision.- Color.- Linear Tools of Vision.- Discrete Images and Hilbert Spaces.- Continuous Functions and Hilbert Spaces.- Finite Extension or Periodic Functions—Fourier Coefficients.- Fourier Transform—Infinite Extension Functions.- Properties of the Fourier Transform.- Reconstruction and Approximation.- Scales and Frequency Channels.- Vision of Single Direction.- Direction in 2D.- Direction in Curvilinear Coordinates.- Direction in ND, Motion as Direction.- World Geometry by Direction in N Dimensions.- Vision in Multiple Directions.- Group Direction and N-Folded Symmetry.- Grouping, Segmentation, and Region Description.- Reducing the Dimension of Features.- Grouping and Unsupervised Region Segregation.- Region and Boundary Descriptors.- Concluding Remarks.
