Abstract
Edge detection is the key to image processing and has a significant impact on the high level of description, classification and matching of subsequent images. The traditional Canny algorithm requires human intervention in the selection of Gaussian function and its fixed parameters. To solve these problems, an improved algorithm based on Canny algorithm is proposed in this paper. The approach introduces the edge preserving filter to replace the original Gaussian filter, and calculates the magnitude and direction of image gradient with a new designed templates from x direction, y direction, and two oblique directions (45°, 135°). Meanwhile, the Otsu algorithm is used to calculate the thresholds, which avoids the problem that the thresholds need to be set repeatedly. The proposed method is successfully applied to the metal plate detection system. Experimental results show that the algorithm has good performance in bright and dark domains.
This work was supported by Natural Science Foundation of China (61403244), Science and Technology Commission of Shanghai Municipality under “Yangfan Program” (14YF1408600, 16YF1403700), Key Project of Science and Technology Commission of Shanghai Municipality (15411953502).
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Yang, A., Jiang, W., Chen, L. (2017). An Adaptive Edge Detection Algorithm Based on Improved Canny. In: Fei, M., Ma, S., Li, X., Sun, X., Jia, L., Su, Z. (eds) Advanced Computational Methods in Life System Modeling and Simulation. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 761. Springer, Singapore. https://doi.org/10.1007/978-981-10-6370-1_56
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DOI: https://doi.org/10.1007/978-981-10-6370-1_56
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