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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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|
|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 (Formerly, School of Automation)|
|Date Deposited:||14 Jun 2006|
|Last Modified:||19 Sep 2010 04:29|
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