A Biologically Plausible Architecture for Shape Recognition

boundary based methods;neural networks;shape recognition

Shetty, Sanketh Vittaldas ; H Joel Trussell, Committee Member,Wesley E. Snyder, Committee Chair,David S. Lalush, Committee Member,Griff Bilbro, Committee Member,Shetty, Sanketh Vittaldas ; H Joel Trussell ; Committee Member ; Wesley E. Snyder ; Committee Chair ; David S. Lalush ; Committee Member ; Griff Bilbro ; Committee Member

University:North Carolina State University

关键词: boundary based methods;    neural networks;    shape recognition;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/1764/etd.pdf?sequence=1&isAllowed=y

美国|英语

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【 摘 要 】

This thesis develops an algorithm for shape representation and matching. The algorithm is an object centered, boundary based method for shape recognition. Global features of the shape are utilized to define a frame of reference relative to which local shape features are characterized. The curvature of the boundary at a point is the local feature used. Curvature is computed by the Digital Straight Segments algorithm. Matching is done using the process of evidence accumulation similar in approach to the Generalized Hough Transform. The algorithm is tested for invariance to similarity transforms. Its robustness to noise and blurring is also tested. A multi-layer, feed-forward neural network architecture that implements the algorithm is proposed.