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Author:

Yu, Naigong (Yu, Naigong.) | Zhang, Zhen (Zhang, Zhen.) | Xu, Qiao (Xu, Qiao.) | Firdaous, Essaf (Firdaous, Essaf.) | Lin, Jia (Lin, Jia.)

Indexed by:

EI Scopus

Abstract:

Image edge detection is the basis for precise positioning and accurate cutting of cloth pattern contours. Compared with the commonly used traditional edge detection methods, the Holistically-nested Edge Detection has clearer and more continuous detection results including the reduction of the false detection rate. However, this method extracts a coarser thick outline. In order to extract a high-precision cloth pattern outline, clearly distinguish the main body of the pattern from the background, provide convenience for the follow-up cutting machine for accurate cutting, this paper proposes an improved method for edge detection of cloth pattern cutting based on the holistically-nested Edge Detection method. The edge refinement and smoothing process are added, where the edge detection, edge refinement, and edge smoothing of the clothes images are carried out in sequences, so that the extracted cloth pattern contour is continuous, smooth, and detailed, allowing the respect of the cutting requirements of the cutting machine and the requirements of the factory production. © 2021 IEEE.

Keyword:

Edge detection Machinery

Author Community:

  • [ 1 ] [Yu, Naigong]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 2 ] [Yu, Naigong]Beijing Key Laboratory of Computing Intelligence and Intelligent System, Beijing; 100124, China
  • [ 3 ] [Yu, Naigong]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 4 ] [Zhang, Zhen]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 5 ] [Zhang, Zhen]Beijing Key Laboratory of Computing Intelligence and Intelligent System, Beijing; 100124, China
  • [ 6 ] [Zhang, Zhen]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 7 ] [Xu, Qiao]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 8 ] [Xu, Qiao]Beijing Key Laboratory of Computing Intelligence and Intelligent System, Beijing; 100124, China
  • [ 9 ] [Xu, Qiao]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 10 ] [Firdaous, Essaf]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 11 ] [Firdaous, Essaf]Beijing Key Laboratory of Computing Intelligence and Intelligent System, Beijing; 100124, China
  • [ 12 ] [Firdaous, Essaf]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 13 ] [Lin, Jia]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 14 ] [Lin, Jia]Beijing Key Laboratory of Computing Intelligence and Intelligent System, Beijing; 100124, China
  • [ 15 ] [Lin, Jia]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China

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Source :

Year: 2021

Page: 1246-1251

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 9

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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