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An improved computing method for the image edge detection

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Abstract

The framework of detecting the image edge based on the sub-pixel multi-fractal measure (SPMM) is presented. The measure is defined, which gives the sub-pixel local distribution of the image gradient. The more precise singularity exponent of every pixel can be obtained by performing the SPMM analysis on the image. Using the singularity exponents and the multi-fractal spectrum of the image, the image can be segmented into a series of sets with different singularity exponents, thus the image edge can be detected automatically and easily. The simulation results show that the SPMM has higher quality factor in the image edge detection.

Newport宣传-MKS新实验室计划
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收稿日期:2006-09-19

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作者单位    点击查看

王刚:School of Science, Nanjing University of Science and Technology, Nanjing 210094School of Physics and Electronics Engineering, Ludong University, Yantai 264025
肖亮:School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094
贺安之:School of Science, Nanjing University of Science and Technology, Nanjing 210094

备注:This work was supported by the Natural Science Foundation of China (No. 60672074), the Natural Science Foundation of Jiangsu Province (No. BK2006569), the Post Doctor Research Foundation of China (No. 20060390285 and 20060601005B), and the Youth Foundation of Nanjing University of Science and Technology (No. NJUST200401). G. Wang's e-mail address is happy_wg@163.com

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引用该论文

王刚, 肖亮, 贺安之, "An improved computing method for the image edge detection," Chinese Optics Letters 5(2), 79-81 (2007)

被引情况

【1】刘小刚,赵慧洁,李娜. 基于多重分形谱的高光谱数据特征提取. 光学学报, 2009, 29(3): 844-847

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