A fractional differential-based approach for edge detection

被引：0
|
作者：
Chen, Dali [1 ]
Xue, Dingyu [1 ]
Chen, Yangquan [2 ]
机构：
[1] Information Science and Engineering, Northeastern University, Shenyang 110006, China
[2] MESA Lab., University of California, 5200 North Lake Road Merced, Merced, CA 95343, United States
来源：
Journal of Computational Information Systems | 2013年 / 9卷 / 23期
关键词：
Calculations - Signal detection - Differentiation (calculus) - Frequency domain analysis - Image enhancement;
D O I：
10.12733/jcis7819
中图分类号：
学科分类号：
摘要：
A fractional differential-based method is proposed for edge detection in the paper. The image edge is estimated by using Riemann-Liouville fractional-order differential definition instead of the derivative of Gaussian kernel, so the accuracy and robustness of the edge detection algorithm are improved. The fractional-order differential mask is proposed and then analyzed in frequency domain. The evaluation method is introduced to evaluate the edge detection method. Finally, a large number of numerical experiments demonstrate that the proposed edge detection algorithm achieves good performance. Copyright © 2013 Binary Information Press.
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页码：9515 / 9522
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