Chinese Journal of Lasers, Volume. 46, Issue 1, 102001(2019)
Feature Points Extraction of Laser Vision Weld Seam Based on Genetic Algorithm
Fig. 3. Image preprocessing effect. (a) Original image of weld laser detection; (b) median filtering results; (c) threshold segmentation results with Otsu method
Fig. 4. Extraction and filling of connected domain. (a) Extraction result; (b) filling result
Fig. 5. Extraction and filling of connected domain in complex noise environments. (a) Original image; (b) connected domain filling result
Fig. 6. Scanning line position determination diagrams. (a) α∈[0°,90°); (b) α=90°; (c) α∈(90°,180°)
Fig. 7. Flow chart of laser stripe skeleton extraction based on genetic algorithm
Fig. 11. Field working diagram of laser vision system. (a) To be welded; (b) welding
Fig. 12. Representative images collected during the test. (a) Proposed method; (b) Hough method
Fig. 13. Statistical graph of weld feature points extraction deviation. (a) Proposed method; (b) Hough method
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Zhang Bin, Chang Sen, Wang Ju, Wang Qian. Feature Points Extraction of Laser Vision Weld Seam Based on Genetic Algorithm[J]. Chinese Journal of Lasers, 2019, 46(1): 102001
Category: laser manufacturing
Received: Jul. 9, 2018
Accepted: --
Published Online: Jan. 27, 2019
The Author Email: Bin Zhang (zhwwbin@cjlu.edu.cn)