Using a progressive intuitive/mathematical approach, this introduction to computer vision provides necessary theory and examples for practitioners who work in fields where significant information must be extracted automatically from images-- including those interested in multimedia, art and design, geographic information systems, and image databases, in addition to the traditional areas of automation, image science, medical imaging, remote sensing and computer cartography. The book provides a basic set of fundamental concepts, (representations of image information, extraction of 3D scene information from 2D images, etc.) algorithms for analyzing images, and discusses some of the exciting evolving application areas of computer vision. The approach is language and software independent, and includes two significant commercial case studies.Imaging and Image Representation. Binary Image Analysis. Pattern Recognition Concepts. Filtering and Enhancing Images. Color and Shading. Texture. Content-Based Image Retrieval. Motion from 2D Image Sequences. Image Segmentation. Matching in 2D. Perceiving 3D from 2D Images. 3D Sensing and Object Pose Computation. 3D Models and Matching. Virtual Reality. Case Studies.For practitioners in any field where information must be extracted automatically from images.
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IMAGING AND IMAGE REPRESENTATION
BINARY IMAGE ANALYSIS
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2D image 3D object 3D points affine transformation algorithm analysis application array axis basis vectors binary image boundary camera camera matrix Chapter clusters color images column computer vision connected components constraints coordinate system corner corresponding curve database defined Definition detected digital image dot product edge encoding Equation error example Exercise extracted feature points filter focus feature frames function gradient gray-tone grid Haralick hash table histogram Hough transform human IEEE image plane image points input image intensity interpretation labeled image light line segments machine vision mapping mask matching matrix methods motion field motion vectors neighborhood node obtained occluding operator output image pairs parameters pattern picture function pixels problem procedure produce quadtree region representation represented retrieval rotation samples scale scene sensor sequence shape shown in Figure shows smooth space spatial stereo surface element surface normal texture threshold trajectories values