Author Affiliations
1Department of Electrical Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China2Shanghai Fangling Computer Software Co., Ltd., Shanghai 200240, China3School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, Chinashow less
Fig. 1. Laser stripe that breaks due to surface contamination of the object being measured (simulation)
Fig. 2. Laser stripe disturbed by light spot (simulation)
Fig. 3. Laser stripe disturbed by sparks (simulation)
Fig. 4. Demonstration of density clustering algorithm. (a) Pixelated laser stripe image; (b) analysis of density clustering for local laser stripe image
Fig. 5. Pseudo-code of density clustering algorithm for binary image
Fig. 6. Demonstration of density clustering algorithm to repair broken stripe, ε=3, P=4
Fig. 7. Graph data structure based on core points
Fig. 8. Demonstration of broken stripe processing. (a) Enlarged view of simulated broken stripe interference; (b) experimental results on broken laser stripe
Fig. 9. Experimental results of light spot interference
Fig. 10. Experimental results of spark interference
Fig. 11. Enlarged view of the dotted framed area of Fig. 10
Fig. 12. Errors of different disturbed image extraction results relative to the reference centerline
Fig. 13. Extraction results of the proposed algorithm when applied to the actual stripe images. (a)--(d) Original images; (e)--(h) enlarged views
Table 1. Parameter setting of density clustering algorithm during experiment
Picture | Wholeregion | Normalregion | Noisedregion | Noised region(image seam) |
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Fig. 1 | 0.423 | 0.371 | 0.807 | 2.028 | Fig. 2 | 0.367 | 0.362 | 0.399 | 1.952 | Fig. 3 | 0.384 | 0.362 | 0.455 | 1.306 |
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Table 2. RMSE of the disturbed image extraction results relative to the reference centerlineunit:pixel
Picture | Image seamalgorithm | Proposedalgorithm |
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Fig. 1 | 257.13 | 6.26 | Fig. 2 | 248.12 | 24.30 | Fig. 3 | 247.94 | 25.33 |
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Table 3. Comparison of the average running time of different algorithmsunit:ms
Picture | Image seamalgorithm | Proposedalgorithm |
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Fig. 13(a) | 123.69 | 9.03 | Fig. 13(b) | 126.82 | 6.13 | Fig. 13(c) | 120.58 | 10.26 | Fig. 13(d) | 70.90 | 20.76 |
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Table 4. Comparison of the average running time of different algorithms used for practical imagesunit:ms