ColorED: Color edge and segment detection by Edge Drawing (ED) |
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Affiliation: | 1. School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;2. Nanjing University of Information Science and Technology, Nanjing 210044, China;1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;2. School of Computer Science and Technology, Huaqiao University, Xiamen 361021, China;3. Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau;4. School of Electro-Mechanical Engineering, Xidian University, Xi’an 710071, China;5. Advanced Manufacturing Institute, King Saud University, Riyadh 11421, Saudi Arabia;6. Industrial Engineering Department, College of Engineering, King Saud University, Saudi Arabia |
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Abstract: | We extend our recent edge and segment detector, Edge Drawing (GrayED), to detect edge segments in color images. Edge Drawing for color images, named ColorED, takes in a color image, and outputs a set of edge segments, each a contiguous, 1-pixel wide chain of pixels. Detected edge segments are then passed through an ‘a contrario’ validation step due to the Helmholtz principle to eliminate perceptually invalid detections. We quantitatively evaluate ColorED with different colorspaces and vector gradient operators within the precision-recall framework of the widely-used Berkeley Segmentation Dataset and Benchmark (BSDS300), and compare its results with those of GrayED and a color version of the Canny edge detector named ColorCanny. We conclude that color edge detection is in general superior to grayscale edge detection, and that ColorED with edge segment validation (ColorEDV) greatly outperforms GrayED, ColorED, and ColorCanny, producing an F-score of 0.6593 with DiZenzo and 0.6747 with the Compass operator while taking an average time of 31.5 ms for BSDS300. |
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Keywords: | Color edge detection Edge Drawing (ED) Vector gradient operators Compass Edge segment validation Helmholtz principle |
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