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A second application area in computer vision is in industry, sometimes called machine vision, where information is extracted for the purpose of supporting a production process. One example is quality control where details or final products are being automatically inspected in order to find defects.
ISBN 0-8493-8524-5. 1st edition:, 2nd edition: ISBN 1-58488-301-4. In its organization, the book resembles the classical handbook in algorithms, Introduction to Algorithms, in its comprehensiveness, only restricted to discrete and computational geometry, computational topology, as well as a broad range of their applications. The second edition ...
Computer Vision. Prentice Hall. ISBN 0-13-030796-3. Gang Xu and Zhengyou Zhang (1996). Epipolar geometry in Stereo, Motion and Object Recognition. Kluwer Academic Publishers. ISBN 0-7923-4199-6. Szeliski, Richard (2022). Computer Vision: Algorithms and Applications (2 ed.). Springer Nature. p. 925. ISBN 3030343723
Download as PDF; Printable version; In other projects ... Second, we find a projective ... Computer Vision: Algorithms and Applications, Section 11.1.1 "Rectification ...
The following is a non-complete list of applications which are studied in computer vision. In this category, the term application should be interpreted as a high level function which solves a problem at a higher level of complexity. Typically, the various technical problems related to an application can be solved and implemented in different ways.
USC Iris computer vision conference list; Computer vision papers on the web A complete list of papers of the most relevant computer vision conferences. Computer Vision Online News, source code, datasets and job offers related to computer vision. Keith Price's Annotated Computer Vision Bibliography; CVonline Bob Fisher's Compendium of Computer ...
When a computer vision system or computer vision algorithm is designed the choice of feature representation can be a critical issue. In some cases, a higher level of detail in the description of a feature may be necessary for solving the problem, but this comes at the cost of having to deal with more data and more demanding processing.
In computer vision, blob detection methods are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, compared to surrounding regions. Informally, a blob is a region of an image in which some properties are constant or approximately constant; all the points in a blob can be considered in some sense ...