Softcover reprint of the original 1st ed. 1994, XII, 218 p.
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Biological visual systems employ massively parallel processing to perform real-world visual tasks in real time. A key to this remarkable performance seems to be that biological systems construct representations of their visual image data at multiple scales. APyramid Framework for Early Vision describes a multiscale, or `pyramid', approach to vision, including its theoretical foundations, a set of pyramid-based modules for image processing, object detection, texture discrimination, contour detection and processing, feature detection and description, and motion detection and tracking. It also shows how these modules can be implemented very efficiently on hypercube-connected processor networks. A Pyramid Framework for Early Vision is intended for both students of vision and vision system designers; it provides a general approach to vision systems design as well as a set of robust, efficient vision modules.
Introduction. Hierarchical Frameworks for Early Vision. 2.1. Hierarchical Processing. 2.2. Hierarchical Multiresolution. 2.3. The Pyramid Architecture. Pyramid Based Visual Modules. 3.1. Introduction. 3.2. Preprocessing and Enhancement. 3.3. Subpopulation and Cluster Detection. 3.4. Region Detection and Delineation: Connected Components. 3.5. Region Detection and Delineation: Compact Regions. 3.6. Contour Representation and Extraction. 3.7. Textured Images. 3.8. Dynamic Images. Integration and Extensions. 4.1. Integration of Visual Modules. 4.2. Extensions. 4.3. The Data Driven Pyramid. 4.4. Conclusions. References. Index.