Share Email Print
cover

Proceedings Paper

3D fabric feature extraction and defect classification using low-cost USB camera
Author(s): Fikri Akbar; Habibullah Akbar; Nanna Suryana; Muhammad Husni
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Defect detection on industrial product using vision system currently is considered as necessity. Quality control of product requires several key factors. Consistency of detection is one of the crucial factors in quality control. Previous method of defect detection requires human assistance. Vision system is the alternative solution for the inconsistent human-based detection. This article discusses defect detection, defect feature extraction and defect classification of fabric product. The solution proposed is by using statistical filter for defect recognition. Extracted features are GLCM-based features, and the proposed 3D defect feature. Defect classification is carried out using Neural Network. The result shows a promising result towards classifying defect product.

Paper Details

Date Published: 30 September 2011
PDF: 6 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 828513 (30 September 2011); doi: 10.1117/12.913388
Show Author Affiliations
Fikri Akbar, Univ. Teknikal Malaysia Melaka (Malaysia)
Habibullah Akbar, Univ. Teknikal Malaysia Melaka (Malaysia)
Nanna Suryana, Univ. Teknikal Malaysia Melaka (Malaysia)
Muhammad Husni, Univ. Teknikal Malaysia Melaka (Malaysia)


Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)
Yi Xie; Yanjun Zheng, Editor(s)

© SPIE. Terms of Use
Back to Top