Abhijit Patil

Papers

Total Citations

H-Index

About

Abhijit Patil is a researcher in biometrics and computer vision, with a focus on developing non-invasive, automated identification systems. His most-cited work, "Automatic Human Gender Identification Using Palmprint" (2019), has garnered 9 citations, establishing a foundation for using palmprint patterns as a reliable biometric trait for gender classification. This contribution addresses a critical gap in forensic and security applications, where rapid, contactless identification is essential. Patil’s research integrates machine learning and image processing techniques to extract distinctive features from palmprints, demonstrating high accuracy and efficiency. Beyond gender identification, his work explores broader biometric authentication methods, aiming to enhance security systems in real-world scenarios. By leveraging palmprint’s uniqueness and accessibility, Patil’s studies offer a cost-effective alternative to traditional fingerprint or facial recognition, particularly in low-resource settings. His findings have implications for surveillance, access control, and demographic analysis, making his research valuable to both academic and industrial communities. As a rising voice in biometrics, Patil continues to push the boundaries of automated human recognition, with his palmprint work serving as a stepping stone for future innovations in identity verification.