Universiti Teknologi Malaysia Institutional Repository

Image enhancement technique at different distance for Iris recognition

Hassan, R. and Kasim, S. and Jafery, W. A. Z. W. C. and Shah, Z. A. (2017) Image enhancement technique at different distance for Iris recognition. International Journal on Advanced Science, Engineering and Information Technology, 7 (4-2). pp. 1510-1515. ISSN 2088-5334

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Official URL: http://dx.doi.org/10.18517/ijaseit.7.4-2.3392

Abstract

Capturing eye images within visible wavelength illumination in the non-cooperative environment lead to the low quality of eye images. Thus, this study is motivated to investigate the effectiveness of image enhancement technique that able to solve the abovementioned issue. A comparative study has been conducted in which three image enhancement techniques namely Histogram Equalization (HE), Adaptive Histogram Equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) were evaluated and analysed. UBIRIS.v2 eye image database was used as a dataset to evaluate those techniques. Moreover, each of enhancement techniques was tested against the different distance of eye image captured. Results were compared in terms of image interpretation by using Peak-Signal Noise Ratio (PSNR), Absolute Mean Brightness Error (AMBE) and Mean Absolute Error (MAE). The effectiveness of the enhancement techniques on the different distance of image captured was evaluated using the False Acceptance Rate (FAR) and False Rejection Rate (FRR). As a result, CLAHE has proven to be the most reliable technique in enhancing the eye image which improved the localization accuracy by 7%. In addition, the results showed that by implementing CLAHE technique at a four-meter distance was an ideal distance to capture eye images in a non-cooperative environment where it provides high recognition accuracy, 74%.

Item Type:Article
Uncontrolled Keywords:histogram equalization, image enhancement, iris recognition
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:81265
Deposited By: Narimah Nawil
Deposited On:23 Jul 2019 08:55
Last Modified:23 Jul 2019 08:55

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