Abstract
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.
Highlights
A biometric identification system identifies automatically an individual based on his physical or behavioral characteristics [1, 2]
Palmprint is one of the most important physiological modalities, and it can be used for personal identification [3, 4]
The palmprint provides a lot of information that can be used in personal identification [4, 6]
Summary
A biometric identification system identifies automatically an individual based on his physical or behavioral characteristics [1, 2]. Palmprint is one of the most important physiological modalities, and it can be used for personal identification [3, 4]. The palmprint provides a lot of information that can be used in personal identification [4, 6]. The usage of the palmprint for identification has attracted increasing attention from researchers [2, 7]. If compared with the finger, palmprint area is larger [2, 8], and contains more features [1, 9]. Palmprint-based biometric systems are lowcost [8], user-friendly [7], and provides high accuracy and efficiency [2]. Many researchers have observed the effectiveness and usefulness of palmprint in identification, only a few works have been reported in improving palmprint identification for individualization purposes [10]
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