Automated Deform Detection On Automotive Body Panels Using Gradient Filtering And Fuzzy C-Mean Segmentation
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 consequ...
محفوظ في:
| المؤلفون الرئيسيون: | , , , |
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| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Penerbit UTM Press
2016
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.utem.edu.my/id/eprint/17099/1/Automated%20Deform%20Detection%20On%20Automotive%20Body%20Panels%20Using%20Gradient%20Filtering%20And%20Fuzzy%20C-Mean%20Segmentation.pdf http://eprints.utem.edu.my/id/eprint/17099/ |
| الوسوم: |
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| الملخص: | 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. |
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