Robust hough-based symbol recognition using knowledge-based hierarchical neural networks

TitleRobust hough-based symbol recognition using knowledge-based hierarchical neural networks
Publication TypeConference Paper
Year of Publication2008
AuthorsWong, A., W. Bishop, and H. R. Arabnia
Conference Name2008 International Conference on Image Processing, Computer Vision, and Pattern Recognition
PublisherCSREA Press
ISBN Number1-60132-078-7
Keywordshierarchical neural networks, hough transform, symbol recognition

A robust method for symbol recognition is presented that utilizes a compact signature based on a modified Hough Transform (HT) and knowledge-based hierarchical neural network structure. Relative position and orientation information is extracted from a symbol image using a modified Hough Transform (HT). This information is transformed and compressed into a compact, 1-D signature vector that is invariant to geometric transformations such as translation, rotation, scaling, and reflection. The proposed method uses a knowledge-based hierarchical neural network structure to reduce the complexity of the recognition process by effectively segmenting the search space into smaller and more manageable clusters based on a priori knowledge. The method achieved overall recognition rates of 96.7% on line graphic symbols from the GREC’05 symbol database under various models of image degradation and distortion.