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2008

Robust Hough-Based Symbol Recognition Using Knowledge-Based Hierarchical Neural Networks

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Robust Hough-Based Symbol Recognition Using Knowledge-Based Hierarchical Neural Networks
Abstract - 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.
Alexander Wong, William Bishop
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where IPCV
Authors Alexander Wong, William Bishop
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