Wang, Wu and Sitharama, Iyengar S and Patnaik, LM (1989) Memory-based reasoning approach for pattern recognition of binary images. In: Pattern Recognition, 22 (5). pp. 505-518.Full text not available from this repository.
Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Elsevier Science.|
|Keywords:||Pattern recognition;Binary image;Memory-based reasoning;The Connection Machine;Multiresolution;Massively parallel processing;Image representation;Template matching.|
|Department/Centre:||Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)|
|Date Deposited:||05 Aug 2010 04:34|
|Last Modified:||05 Aug 2010 04:34|
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