Welding flame detection based on color recognition and progressive probabilistic Hough transform. (10th June 2020)

• Record Type: Journal Article
• Authors: Chen, Weiming; Chen, Siqi; Guo, Hailin; Ni, Xiaoyang
• Is Part Of: Concurrency and computation. Volume 32:Number 19(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-10
• Subjects: HSV color space -- the progressive probabilistic Hough transform -- unsafe behavior -- welding flame; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5815
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Welders are widely used in machinery manufacturing and machining industry. In the process of electric welding, accidents are often caused by some unsafe behaviors. This paper focuses on the intelligent recognition method of welding flame, which can reduce the accidents of welding flame to a certain extent. Due to the difficulties in observing workers on job sites, developing an algorithm for intelligent identification of unsafe factors is significant. Firstly, Hue, Saturation and Value (HSV) color space with strong robustness is selected to segment the mark image with threshold value, and the region of interest in which the welding fame is located is segment; secondly, the Progressive Probabilistic Hough transform is used to detect the region of interest, judge the number of existing lines, and finally determine whether there is welding flame in this region. In this way, the welding flame can be better detected, which can reduce the workload of managers and is beneficial to the supervision of the management personnel.