Model-guided attributed string matching by split-and-merge for shape recognition

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题名:	Model-guided attributed string matching by split-and-merge for shape recognition
作者:	Y. T. Tsay;W. H. Tsai
贡献者:	Department of Information Communication
关键词:	Shape analysis;Attributed string matching;Split-and-merge;Polygon approximation
日期:	1989
上传时间:	2009-11-25 02:30:50 (UTC+0)
出版者:	Asia University
摘要:	Due to noise and distortion, segmentation uncertainty is a key problem in structural pattern analysis. In this paper we propose the use of the split operation for shape recognition by attributed string matching. After illustrating the disadvantage of attributed string matching using the merge operation, the split operation is proposed. Under the guidance of the model shape, an input shape can be reapproximated, using the split operation, into a new attributed string representation. By combining the split and the merge operations for shape matching it is unnecessary to apply any type of edit operation to a model shape. This makes the distance between the input shape and the model shape more meaningful and stable, and improves recognition results. An algorithm for attributed string matching by split-and-merge is proposed. To eliminate the effect of the numbers of primitives in the model shape on the shape distance, shape recognition based on a similarity measure is also proposed. Good experimental results prove the feasibility of the proposed approach for general shape recognition.
關聯:	International Journal of Pattern Recognition and Artificial Intelligence 4 (2): 159-179
显示于类别:	[資訊傳播學系] 期刊論文

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