Steel surface in-line inspection using machine vision

Hsiao-Wei Liu; Yu-Ying Lan; Han-Wen Lee; Ding-Kun Liu

doi:10.1117/12.2242965

11 July 2016 Steel surface in-line inspection using machine vision

Hsiao-Wei Liu, Yu-Ying Lan, Han-Wen Lee, Ding-Kun Liu

Proceedings Volume 10011, First International Workshop on Pattern Recognition; 100110X (2016) https://doi.org/10.1117/12.2242965
Event: First International Workshop on Pattern Recognition, 2016, Tokyo, Japan

Abstract

A roll of steel might have various defects of scratch, stains, and chisel mark after slitting process. However, the traditional steel surface inspection method is via the human inspection that not only takes amount of time but also causes inconsistent inspection consequences. As a result, this paper proposed an in-line visual inspection hardware and software system. The hardware is composed of upper and lower optical module. The defect inspection algorithm includes automatic region of interesting (ROI) searching and defect detection by using Sobel method. Experimentations revealed that the successful detection rate is up to 80% and the inspection speed of per image with 3K in width and 1K in length is less than 80 milliseconds. The contribution is that the proposed method can provide suitable inspection results of the steel surface defect and meet the steel industry demands.

Citation Download Citation

Hsiao-Wei Liu, Yu-Ying Lan, Han-Wen Lee, and Ding-Kun Liu "Steel surface in-line inspection using machine vision", Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100110X (11 July 2016); https://doi.org/10.1117/12.2242965

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