Palmprint has become one of the biometric modalities that can be used for personal identification. This modality contains critical identification features such as minutiae, ridges, wrinkles, and creases. In this research, feature from creases will be our focus. Feature from creases is a special salient feature of palmprint. It is worth noting that currently, the creases-based identification is still not common. In this research, we proposed a method to extract crease features from two regions. The first region of interest (ROI) is in the hypothenar region, whereas another ROI is in the interdigital region. To speed up the extraction, most of the processes involved are based on the processing of the image that has been a downsampled image by using a factor of 10. The method involved segmentations through thresholding, morphological operations, and the usage of the Hough line transform. Based on 101 palmprint input images, experimental results show that the proposed method successfully extracts the ROIs from both regions. The method has achieved an average sensitivity, specificity, and accuracy of 0.8159, 0.9975, and 0.9951, respectively.

In this paper, two shadow reduction algorithms have been proposed and implemented using CIE Lab color space. The task of performing shadow reduction is done by executing shadow detection, shadow removal and lastly shadow edge correction in a sequential order. The first proposed algorithm is implemented based on pixel illumination and color information meanwhile the second algorithm is carried out via thresholding of one or more CIE Lab color space channels. The outputs from both proposed algorithms are compared in terms of shadow detection accuracy and required processing period. The proposed methods shown some promising results.

No abstract

Abstract-In this paper, two shadow reduction algorithms have been proposed and implemented using CIE Lab color space. The task of performing shadow reduction is done by executing shadow detection, shadow removal and lastly shadow edge correction in a sequential order. The first proposed algorithm is implemented based on pixel illumination and color information meanwhile the second algorithm is carried out via thresholding of one or more CIE Lab color space channels. The outputs from both proposed algorithms are compared in terms of shadow detection accuracy and required processing period. The proposed methods shown some promising results.