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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/59897


    Title: Edge Detection Improvement by Ant Colony Optimization
    Authors: 陳建彰;盧德賢
    Contributors: 淡江大學資訊工程學系
    Keywords: Edge detection;Ant colony optimization (ACO);Pheromone trail
    Date: 2008-04-01
    Issue Date: 2011-10-05 22:25:01 (UTC+8)
    Abstract: Edge detection is a technique for marking sharp intensity changes, and is important in further analyzing image content. However, traditional edge detection approaches always result in broken pieces, possibly the loss of some important edges. This study presents an ant colony optimization based mechanism to compensate broken edges. The proposed procedure adopts four moving policies to reduce the computation load. Remainders of pheromone as compensable edges are then acquired after finite iterations. Experimental results indicate that the proposed edge detection improvement approach is efficient on compensating broken edges and more efficient than the traditional ACO approach in computation reduction.
    Relation: Pattern Recognition Letters 29(4), pp.416-425
    DOI: 10.1016/j.patrec.2007.10.021
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

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