Analysis of contrast limited adaptive histogram equalization (CLAHE) parameters on finger knuckle print identification

Abstract

Recently, safe and reliable identification systems are strongly needed. One of them is Biometric Identification System. A Biometric characterization of Finger Knuckle Print ( FKP) that a person has is unique.A method to improve image enhancement is needed in order to produce a better and clearer image. Contrast Limited Adaptive Histogram Equalization (CLAHE) is an image enhancement method that can provide clip limit and region size. This research proves that changes in the region size and clip limit parameters can affect the accuracy of the finger knuckle print biometric identification by extracting Speeded-Up Robust Features (SURF) and PrincipalComponentAnalysis (PCA) features. The highest accuracy using SURF extraction is obtained at region size 5x5 and clip limit 0.14 which is 97%, while the highest accuracy with PCA feature extraction is obtained when the region size is 2x2 and clip limit is 0.12, 0.13, 0.14, 0.15, 0.18, 0.2, 0.4, and 0.8 which is 91%.