Automated Model-Based Computer Vision

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This project addresses a key problem which currently limits the success of machine vision in new applications: design of algorithms. Methods are explored to partially automate the design of vision algorithms for recognizing and localizing industrial parts and other man-made objects. The project suggests a unified methodology for partially automating the generation of vision algorithms using methodologies of search, reasoning under uncertainty, perspective geometry analysis, and especially mathematic morphology. The work also addresses the important software-related issue of testing and evaluation of vision algorithms. The results should find use in industrial, military, and space applications.