Oil seal surface defect detection using superpixel segmentation and circumferential difference. (7th December 2020)

• Record Type: Journal Article
• Authors: He, Zhendong; Liu, Jie; Jiang, Liying; Zhao, Suna; Zhang, Lei; Cui, Liangjian
• Is Part Of: International journal of advanced robotic systems. Volume 17:Number 6(2020:Nov./Dec.)
• Publication Date: 2020-12-07
• Subjects: Superpixel segmentation -- circumferential difference -- contrast enhancement -- oil seal -- surface defect detection; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881420976511
• Languages: English
• ISSNs: 1729-8806

Abstract

Surface defects affect the quality and safety of oil seals. It is a challenge to detect such defects in a vision system because of the unequal reflection property of oil seal surfaces and low contrast between the defect and the background. This article proposes a visual detection method (VDM) for oil seal surface defects and outlines two key issues of VDMs. First, we present a superpixel segmentation algorithm based on the significant gray level variation in the radial direction of an oil seal surface image. This image is then divided into several ring belts. Subsequently, considering the reflection inequality and low contrast, we propose a new circumferential background difference algorithm based on the small variation along the circumferential direction of the image. This algorithm eliminates the influence of the reflection inequality and improves the contrast distinction between the defects and the background. The experimental results verify the effectiveness of the proposed method with a recall and precision as high as 95.2% and 86.8%, respectively.