Laser & Optoelectronics Progress, Volume. 58, Issue 16, 1630006(2021)
Wire Rope Defect-Detection Method Based on Otsu Segmentation and Edge Detection
Fig. 1. Wire rope detection system
Fig. 2. Damaged wire rope sample
Fig. 3. Hyperspectral images of wire rope with defects. (a) 410 nm band image; (b) 470 nm band image; (c) 566 nm band image; (d) 661 nm band image; (e) 737 nm band image; (f) 793 nm band image
Fig. 4. Spectral curves of the wire rope area with the defect and the background area. (a) Reflectivity of randomly selected ROIs; (b) two parts of ROI reflectivity after average processing
Fig. 5. Hyperspectral images and gray histograms. (a) 406 nm band image and its grayscale histogram; (b) 566 nm band image and its grayscale histogram; (c) 645 nm band image and its grayscale histogram
Fig. 6. Image threshold segmentation results at different wavelengths. (a) 406 nm band image; (b) 566 nm band image; (c) 645 nm band image
Fig. 7. Comparison of edge detection results based on different operators. (a) Roberts operator; (b) Sobel operator; (c) Prewitt operator; (d) Canny operator
Fig. 8. Hyperspectral images after Hough transform. (a) Based on Roberts operator; (b) based on Sobel operator; (c) based on Prewitt operator; (d) based on Canny operator
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Ruochen Dai, Mingfu Zhao, Bin Tang, Liyong Dai, Taojiang Wu, Shanghai Jiang. Wire Rope Defect-Detection Method Based on Otsu Segmentation and Edge Detection[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1630006
Category: Spectroscopy
Received: Sep. 8, 2020
Accepted: Oct. 21, 2020
Published Online: Aug. 16, 2021
The Author Email: Tang Bin (tangbin@cqut.edu.cn)