Palmprint ROI Cropping Based on Enhanced Correlation Coefficient Maximisation Algorithm

Abstract

This paper proposes new technique to extract the Region of Interest (ROI) of palmprint biometric image while removing the distortion between images such as translation or rotation during ROI extraction. A similarity measure known as Enhanced Correlation Coefficient (ECC) is used in the proposed approach for better ROI extraction and image alignment, which helps to evaluate and determine the distortion. The objective of image alignment approaches are to find the deformation or transformation that minimizes the incongruities between images. After applying ECC algorithm the Region of Interest (ROI) is extracted from the palmprint by using moore neighbors algorithm, on the other hand, to verify and validate the efficacy of the recommended method the PolyU palmprint dataset II was used. The results show the high accuracy is 99.8% in deriving the ROI and developing a robust ROI cropping system successfully.