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@article{190715,
        author = {Samadhan ghodke and Prapti D. Deshmukh and Anand kadam and Manisha B. More and Shalini B. bakal and Akshay P. Deshpande},
        title = {Acquisition of Facial Images for Biometrics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {3251-3255},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190715},
        abstract = {Facial image acquisition is a critical component of biometric authentication and identification systems, yet remains challenging in unconstrained real-world environments. This paper provides a comprehensive analysis of facial image acquisition techniques, standards, and challenges for biometric applications. We examine current international standards (ISO/IEC 19794-5), preprocessing methodologies, and practical implementation challenges including variable lighting, pose variations, occlusions, and low-resolution imagery. We present empirical findings from recent surveillance and access control implementations, demonstrating that effective quality assessment frameworks can reduce false rejection rates by up to 99.7%. Our review of state-of-the-art approaches reveals that integration of automated quality assessment with deep learning-based face detection achieves optimal performance in constrained and unconstrained scenarios. Future directions include adaptation to emerging IoT-based systems and real-time mobile biometric applications.},
        keywords = {Facial image acquisition, Biometric authentication, Image preprocessing, Face detection, Quality assessment, ISO standards.},
        month = {January},
        }