A Blind Blur Detection Scheme Using Statistical Features of Phase Congruency and Gradient Magnitude. (15th July 2014)

• Record Type: Journal Article
• Authors: Tiwari, Shamik; Shukla, V. P.; Biradar, S. R.; Singh, A. K.
• Other Names: Travieso-González Carlos M. Academic Editor.
• Is Part Of: Advances in electrical engineering. Volume 2014(2014)
• Publication Date: 2014-07-15
• Subjects: Electrical engineering -- Periodicals; Electrical engineering; Periodicals; 621.3
• DOI: 10.1155/2014/521027
• Languages: English
• ISSNs: 2356-6655

Abstract

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.