Title: Irregularities recognition system for automotive pieces

Authors: Ignacio Algredo-Badillo; Germàn Portillo-García; Kelsey A. Ramírez-Gutiérrez; Luis A. Morales-Rosales

Addresses: CONACyT, Instituto Nacional de Astrofísica, Ópticay Electrónica, Luis Enrique Erro #1, Santa María Tonatzintla, Puebla, Mexico ' Universidad Politécnica de Tlaxcala, Avenida Universidad Politécnica No. 1, San Pedro Xalcaltzinco, Tlaxcala, Mexico ' CONACyT, Instituto Nacional de Astrofísica, Ópticay Electrónica, Luis Enrique Erro #1, Santa María Tonatzintla, Puebla, Mexico ' CONACyT, Universidad Michoacana de San Nicolas de Hidalgo, Gral. Francisco J. Mugica S/N, Ciudad Universitaria, Morelia, Michoacán, Mexico

Abstract: The automotive industry is a growing sector in Mexico that requires many production processes. One of the most important is auto parts manufacturing with high-quality standards to avoid economic losses. Hence, the failure detection of pieces must be carried out in the early process, discarding those that do not reach the desired quality. This paper deals with an object recognition system to automatically find failures in circular automotive pieces. This is an open problem in the automobile assembly process to guarantee product quality. We detect imperfections (above 3.5 mm) on small pieces, such as scratches and dents on edges, by using an image processing stage, where no training is included, with a low-cost camera. The average processing time to detect failures is 2.7 seconds, which allows us to examine more pieces in a short time compared with other works and with manual inspections carried out by human experts. The proposed system reaches an accuracy of 98% and is implemented in the LabVIEW tool.

Keywords: automotive industry; vehicle pieces; defects detection; Hough transform; irregularities recognition.

DOI: 10.1504/IJCVR.2022.126511

International Journal of Computational Vision and Robotics, 2022 Vol.12 No.6, pp.614 - 631

Received: 28 Sep 2020
Accepted: 07 Sep 2021
Published online: 27 Oct 2022 *

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