Title: Error detection of industrial design product appearance dimensional based on machine vision

Authors: Hua Song

Addresses: Cheung Kong School of Art & Design, Shantou University, Shantou, Guangdong, China

Abstract: Aiming at the problems existing in current methods, such as high false detection rate, low signal-to-noise ratio of image edges and high cost of sub-pixel matching, an error detection method of industrial design product appearance dimension based on machine vision is proposed. The fuzzy algorithm is used to extract the edge of industrial design product appearance image, and the sub-pixel point matching is carried out after determining the amplitude change of sub-pixel points in the edge image. According to the pixel coordinates and image parallax of the appearance image, the standard threshold of the appearance image dimensional of industrial design products is set, and the appearance dimensional image to be detected is compared with the standard threshold of the image dimensional to realise error detection. Test results show that the proposed method has low false detection rate, high signal-to-noise ratio of image edge and low cost of sub-pixel point matching.

Keywords: machine vision; industrial design products; appearance dimensional; error detection; amplitude; sub-pixel point matching.

DOI: 10.1504/IJPD.2025.144853

International Journal of Product Development, 2025 Vol.29 No.1, pp.100 - 119

Received: 05 Mar 2024
Accepted: 14 Nov 2024
Published online: 05 Mar 2025 *

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