Automated Deform Detection On Automotive Body Panels Using Gradient Filtering And Fuzzy C-Mean Segmentation

Muhammad Zuhair Bolqiah, Edris and Zahriladha, Zakaria and Mohd Shahril Izuan, Mohd Zin and Mohammed Saeed, Jawad (2016) Automated Deform Detection On Automotive Body Panels Using Gradient Filtering And Fuzzy C-Mean Segmentation. Jurnal Teknologi, 78 (6-8). pp. 93-99. ISSN 0127-9696

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Abstract

Automatic deform detection on automotive body panel is challenging owing to its localization on a large surface, variation in appearance, and their rare occurrences. It is difficult to detect these deforms either by original models or by small-sample statistics using a single threshold. As a consequence, this problem is focussed to derive a lot of good-quality deform detected from the surface images. These detections should discriminate the various surface deforms when fed to suitable image processing algorithms. This paper used gradient filtering and background illumination correction to identify the deform area. An algorithm to segment the deform area has been developed. It segments the deformation by using Fuzzy C-Means (FCM) segmentation. The algorithm is being test on three samples which are car door model, curve and flat surface with two types of deformations which is ding and dent deformations that occur on the surface.

Item Type:	Article
Uncontrolled Keywords:	Deformation Detection, Segmentation, Gradient Filtering, Fuzzy C-Means thresholding, Otsu thresholding.
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Electronics and Computer Engineering
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	21 Sep 2016 02:41
Last Modified:	09 Sep 2021 00:06
URI:	http://eprints.utem.edu.my/id/eprint/17099
Statistic Details:	View Download Statistic

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