期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2018
卷号：9
期号：2
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Edge detection is a crucial step in various image processing systems like computer vision , patternrecognition and feature extraction. The Canny edge detection algorithm even though exhibits highaccuracy, is computationally more complex compared to other edge detection techniques. A block baseddistributed edge detection technique is presented in this paper, which adaptively finds the thresholds foredge detection depending on block type and the distribution of gradients in each block. A novel method ofcomputation of high threshold has been proposed in this paper. Block-based hysteresis thresholds arecomputed using a non uniform gradient magnitude histogram. The algorithm exhibits remarkably highedge detection accuracy, scalability and significantly reduced computational time. Pratt’s Figure of Meritquantifies the accuracy of the edge detector, which showed better values than that of original Canny anddistributed Canny edge detector for benchmark dataset. The method detected all visually prominent edgesfor diverse block size.
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