Palm Lines Recognition Using Dynamic Image Segmentation

In recent years, there has been growing interest in the scientific exploration of palmistry, viewing it not only as a traditional practice but also as a potential avenue for biometric identification and predictive analysis. This paper presents an innovative approach to identifying and analyzing palm lines through dynamic image segmentation. The research is based on a device's results to capture an individual's palm lines and use it as biometric data for matching and recognition. The research implements Percentage Error as the statistical treatment for the system and algorithm. By leveraging advanced image segmentation techniques, this research aims to deepen our understanding of palm line recognition and explore avenues for enhancing its applications across various fields. The results of this research paper show that the system's accuracy is 88 percent accuracy and 4.84 percent Percentage Error. The accuracy and performance of the system can be improved by using better hardware to support heavier processing and techniques.