Babu, Phanendra G and Murty, Narasimha M (1995) Optimal thresholding using multi-state stochastic connectionist approach. In: Pattern Recognition Letters, 16 (1). pp. 11-18.
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Abstract
In this paper, we describe the applicability of the K-means clustering algorithm for locating thresholds in a given histogram. In order to find optimal thresholds a probabilistic method called Multi-state Stochastic Connectionist Approach (MSCA) is em-ployed. Mean Field Annealing (MFA), a deterministic counterpart of MSCA, is also studied in this context. A parallel model to parallelize the above methods is presented. Results of MFA and MSCA are compared with that of the K-means algorithm.
Item Type: | Journal Article |
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Publication: | Pattern Recognition Letters |
Publisher: | Elsevier |
Additional Information: | The copyright belongs to Elsevier. |
Keywords: | Neural networks;Image processing;Image segmentation:Thresholding;Clustering methods |
Department/Centre: | Division of Electrical Sciences > Computer Science & Automation |
Date Deposited: | 14 Jun 2006 |
Last Modified: | 19 Sep 2010 04:29 |
URI: | http://eprints.iisc.ac.in/id/eprint/7613 |
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