Fuzzy Techniques to Verify A Person's Identification Using the X-Ray Images. Issue 1 (May 2021)

• Record Type: Journal Article
• Authors: Ponprakash, N; Radhakrishnan, K; Manesh, M; Suganya, T
• Is Part Of: Journal of physics. Volume 1916:Issue 1(2021)
• Publication Date: 2021-05
• Subjects: hand radiographs -- biometric information -- fuzzy -- neural network -- clustering; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1916/1/012183
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Biometric x-rays are a means of testing the physical properties of an individual to check their identity. There are anatomical attributes, such as eyes or traits of behavior, fingerprints and a special path to authentication. In this article, the use of a deep neural network with fuzzy clustering is proposed as a new approach for forensic radiography based human authentication. A complex, convolutionary neural architecture is used to derive features of hand x-rays and for the detection of fluid clusters. Our experiment demonstrates that hand x-rays provide fingerprint information to identify individuals. That laboratory analysis shows that the proposed solution is much better than previously existing authentication schemes with hand X-rays.