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@article{180602,
        author = {L.Shravani and B. Shyam and B. Nikhila and K. Trisha and S.T. Saravanan},
        title = {Identical Twin Recognition In Crime Solving Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1659-1664},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180602},
        abstract = {This project pioneers a machine learning approach to distinguish identical twins for crime solving, addressing a significant gap in traditional biometric identification. By employing a "bag of features" methodology, the system leverages face detection and image processing to extract subtle, unique characteristics that differentiate twins. A K-nearest neighbors classifier is then trained on these features, enabling the computer to learn and identify individuals within twin pairs. This work promises to revolutionize forensic investigations and enhance global security by providing a crucial tool for accurate identification in challenging twin-related cases.},
        keywords = {Machine Learning, Biometric Identification, Forensic Science, Face Detection, Image Processing, Feature Extraction, K-Nearest Neighbors (KNN) Classifier.},
        month = {June},
        }