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@article{179069,
        author = {Deepak Raj V R and Akshaya B and Vishalini S and Dr Deepa Natesan},
        title = {Secured Vein Authentication Mechanism on ATM Amount Transactional Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7073-7079},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179069},
        abstract = {With the growing cyber threats and security intrusions, particularly in financial systems, there arises an increasing demand for sophisticated, contactless, and safe biometric authentication techniques. This paper describes a new palm vein-based authentication system tailored to the transactional ATM environment. Utilizing the imaging capability of near-infrared (NIR) light, the system they propose picks up the one-of-a-kind vascular patterns in the human palm with a high degree of security and immunity to duplication and spoofing. Palm vein authentication is a contactless and sanitary process in contrast to conventional biometric systems like fingerprint or facial recognition, which could be very useful for post-pandemic application and public infrastructure. The framework includes a robust image capture and preprocessing pipeline, accurate region-of-interest (ROI) segmentation, aggressive feature extraction with Gabor and LBP filters, and effective classification by regression tree and neural network classifiers. Real-time responsiveness and scalability have been prioritized in the model’s design, with the model maintaining an authentication accuracy of more than 96.3% with an average response time of less than 2.5 seconds.},
        keywords = {Palm vein identification, biometric verification, NIR imaging, ATM protection, neural network, regression tree, feature extraction, SDG, hygienic biometrics, contactless verifi- cation.},
        month = {May},
        }