Biometric technologies, including fingerprinting, iris scanning, and face recognition, have become key tools for identity verification in recent years. Among these, face recognition plays a vital role in identity authentication, especially in security centers, law enforcement agencies, and public places. Alongside advancements in face recognition technologies, criminals’ attempts to conceal their identities through facial alterations have posed a significant security challenge. Despite the growing demand for this technology in Iran, developing efficient and indigenous tools in this field holds particular importance. This research aims to identify and analyze features related to facial changes in face recognition methods based on image processing and machine learning. The results indicate that the Naïve Bayes algorithm achieved an accuracy of 93.30%, and the K-Nearest Neighbors (KNN) algorithm reached an accuracy of 86.30% in detecting facial changes; moreover, a combined method demonstrated superior performance with an accuracy of 96.67%. The findings of this study can contribute to improving the accuracy and efficiency of surveillance and security systems. Emphasizing privacy protection aspects alongside the development of these systems is essential. It is hoped that the results of this research will pave the way for the development of more sophisticated algorithms and implementation of more effective facial change detection systems.
صفری سیدآبادی، ناهید، معتمد، سارا، 1397،بازشناسی چهره با استفاده از مدل بهبود یافتهی HMAX، فصلنامهی تازه های علوم شناختی، سال 21، شماره ی 1، صفحه ی 1-17.
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zolfaghari, M., & Ebrahimi, E. (2024). Providing a combined method of detecting face change using image processing: machine learning approach. protectiv & security researches, 13(50), 187-212.
MLA
mohammad zolfaghari; Ehsan Ebrahimi. "Providing a combined method of detecting face change using image processing: machine learning approach", protectiv & security researches, 13, 50, 2024, 187-212.
HARVARD
zolfaghari, M., Ebrahimi, E. (2024). 'Providing a combined method of detecting face change using image processing: machine learning approach', protectiv & security researches, 13(50), pp. 187-212.
VANCOUVER
zolfaghari, M., Ebrahimi, E. Providing a combined method of detecting face change using image processing: machine learning approach. protectiv & security researches, 2024; 13(50): 187-212.
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