Table of Contents
Advances in Electrical Engineering
Volume 2014 (2014), Article ID 521027, 10 pages
http://dx.doi.org/10.1155/2014/521027
Research Article

A Blind Blur Detection Scheme Using Statistical Features of Phase Congruency and Gradient Magnitude

1FET, Mody University of Science & Technology, Laxmangarh 332311, India
2SDM College of Engineering, Hubli-Dharwad 580001, India

Received 3 April 2014; Revised 3 June 2014; Accepted 17 June 2014; Published 15 July 2014

Academic Editor: Carlos M. Travieso-González

Copyright © 2014 Shamik Tiwari et al. 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

The growing uses of camera-based barcode readers have recently gained a lot of attention. This has boosted interest in no-reference blur detection algorithms. Blur is an undesirable phenomenon which appears as one of the most frequent causes of image degradation. In this paper we present a new no-reference blur detection scheme that is based on the statistical features of phase congruency and gradient magnitude maps. Blur detection is achieved by approximating the functional relationship between these features using a feed forward neural network. Simulation results show that the proposed scheme gives robust blur detection scheme.