Some computational aspects of low-level computer vision

Article Abstract:

Three low-level computer vision problems (2.5-dimensional sketch surface fitting, shape from shading, and optical flow) are evaluated to illustrate some of the computational and algorithmic requirements. These include the existence of, uniqueness of, and optimal solutions; efficient and reliable algorithms, and coping with discontinuities and discretization errors. The application of interpolating-splines and smoothing-splines with discontinuities to surface fitting are evaluated. A convergent iterative algorithm is described for shape from shading and occluding boundaries problems. The Chebyshev iterative method is suggested as a strategy for solving a system of linear equations that define optical flow problems. Details of the algorithms, theorems, and proofs are described.

Algorithms, Image processing, Algorithm, Methods, Shape, Shading

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Computer vision: basic principles

Article Abstract:

Computer vision involves the acquisition and analysis of images in a scene for the purpose of extracting data about it. This overview of the subject addresses the digitization of two- and three-dimensional images, image analysis, and representation by pixels in both grey scales and color. The implementation of computer vision systems addresses the types of image data representation, operations on the data, and the five principle types of multi-processor architectures used. Problems of and outlook in model-based vision, integrated vision, knowledge-based vision, and vision system architectures are also discussed.

Systems analysis, Systems development, Implementation, System Development, System Design, Applications, Data Acquisition Systems

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