Abstract
A novel optimal multilevel thresholding algorithm for image segmentation is presented to deal with RAPD Fingerprint of acinetobacter calcoaceticus-baumannii. The proposed algorithm is an artificial immune network used to optimize multilevel thresholds of image segmentation. In addition, a fast fuzzy clustering technique is used to improve efficiency of the algorithm. Experimental results show that the algorithm can effectively extract fingerprint from the images to facilitate genotyping analysis of RAPD fingerprinting of acinetobacter calcoaceticus-baumannii.
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