Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4692
Title: A quality aware technique for biometric recognition
Authors: Joshi, Piyush
Prakash, Surya
Keywords: Biometrics;Image quality;Absolute difference;Biometric recognition;Contour;De-Noise;Experimental analysis;Gaussian smoothing;Image quality assessment;Recognition process;Image enhancement
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Joshi, P., & Prakash, S. (2015). A quality aware technique for biometric recognition. Paper presented at the 2nd International Conference on Signal Processing and Integrated Networks, SPIN 2015, 795-800. doi:10.1109/SPIN.2015.7095437
Abstract: Noise is a very common factor for degradation of images and for better performance of any image based biometric system, enhancement of poor quality images due to noise is necessary. In most of the previously proposed techniques in the literature, it is assumed that all the images participating in the recognition process are of poor quality and an enhancement technique is blindly applied to all the images to enhance them. For example, apply Gaussian smoothing on all the images to make them noise free, however, such blind application of image enhancement degrades the quality of good images. This paper presents a quality aware technique for biometric recognition. It has utilized our previously proposed technique for image quality assessment based on noise detection. The technique first estimates the quality of the images used in the recognition and if the quality value is found to be below a certain threshold, an enhancement is applied on the image before using it for recognition. Experimental analysis has been conducted on Yale Extended Cropped Face Database. Obtained results show the effectiveness of the proposed technique. © 2015 IEEE.
URI: https://doi.org/10.1109/SPIN.2015.7095437
https://dspace.iiti.ac.in/handle/123456789/4692
ISBN: 9781479959914
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

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