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Automated deform detection on automotive body panels using gradient filtering and Fuzzy C-Mean segmentation
Edris, M.Z.B1, Zakaria, Z2, Zin, M.S.I.M3, Jawad, M.S4.
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.
Affiliation:
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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