| An improved computing method for the image edge detection |
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| 作者姓名： | 王刚 肖亮 贺安之 |
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| 作者单位： | School of Science Nanjing University of Science & Technology Nanjing 210094 School of Physics & Electronics Engineering，Ludong University Yantai 264025，School of Computer Science & Technology Nanjing University of Science & Technology Nanjing 210094，School of Science Nanjing University of Science & Technology Nanjing 210094 |
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| 基金项目： | 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)，the Youth Foundation of Nanjing University of Science and Technology (No. NJUST200401). |
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| 摘 要： | 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.
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