Study on Fur Cutting Path Method Based on Contour Radius Increment Constraint
DOI: 10.23977/jipta.2022.050105 | Downloads: 10 | Views: 708
Author(s)
Linhua Hu 1, Jun Ni 1, Zhengye Wang 1, Shixian Chen 1, Jie Hong 1
Affiliation(s)
1 College of Mechanical and Electrical Engineering, Shaanxi University of Science & Technology, Xi'an, Shaanxi, 710021, China
Corresponding Author
Jun NiABSTRACT
This paper takes the fur edge contour as the research object, and proposes a cutting algorithm based on the incremental constraint of contour radius. The algorithm uses the centroid of the fur contour as the starting point to make rays at the same interval angle, and the distance between the intersection of the ray and the contour point is calculated by the ratio of the radius of the adjacent intersection points. By setting the maximum and minimum thresholds of the growth rate, the intersections exceed the threshold are processed to meet the threshold conditions. Finally, the connection of all the remaining intersections is the cutting path. The experimental results show that the cutting method proposed in this paper can realize the image cutting and give the cutting path, which can meet the industrial production requirements of automatic fur cutting.
KEYWORDS
Local feature description, Contour radius increment constraint, Cutting path planningCITE THIS PAPER
Linhua Hu, Jun Ni, Zhengye Wang, Shixian Chen, Jie Hong, Study on Fur Cutting Path Method Based on Contour Radius Increment Constraint. Journal of Image Processing Theory and Applications (2022) Vol. 5: 29-34. DOI: http://dx.doi.org/10.23977/jipta.2022.050105.
REFERENCES
[1] Hu L, Xiang C, Zhang F. Local feature extraction of sheepskin based on structure contour shape description[C]//MATEC Web of Conferences. EDP Sciences, 2021, 336: 06026.
[2] Ito M. Detecting angles within continuous contours in the early stages of macaque visual cortex[J]. Neuroscience Research, 2010 (68): e381.
[3] ÖZTÜRK M, KAYIKÇIOĞLU T. A model-based edge estimation method with increased edge localization accuracy for medical images[J]. Turkish Journal of Electrical Engineering and Computer Science, 2015, 23(4): 1127-1141.
[4] Salih N D, Ngo D C L, Mellah H. 2D object description with discrete segments[J]. Journal of Computer Science, 2006, 2(7): 572-576.
[5] Lou L, Dan W, Chen J. A threshold selection method based on edge preserving[C]//MIPPR 2015: Automatic Target Recognition and Navigation. International Society for Optics and Photonics, 2015, 9812: 981218.
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