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Journal of Sensors
Volume 2016, Article ID 6506249, 10 pages
http://dx.doi.org/10.1155/2016/6506249
Research Article

A Novel Edge Feature Description Method for Blur Detection in Manufacturing Processes

Department of Information Technology and Communication, Shih Chien University, No. 200, University Road, Neimen, Kaohsiung 84550, Taiwan

Received 21 July 2015; Revised 25 September 2015; Accepted 28 September 2015

Academic Editor: Jesus Corres

Copyright © 2016 Tsun-Kuo Lin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A novel inspection sensor by using an edge feature description (EFD) algorithm based on a support vector machine (SVM) is proposed for industrial inspection of images. This method detects and adaptively segments blurred images by using the proposed algorithm, which uses EFD to effectively classify blurred samples and improve the conventional methods of inspecting blurred objects; the algorithm selects and optimally tunes suitable features. The proposed sensor applies a suitable feature-extraction strategy on the basis of the sensing results. Experimental results demonstrate that the proposed method outperforms the existing methods.