A Machine Learning Access for Person Identification using Dental X-Ray Images
Pratik S. Meshram1, Dhanashree K. Parate2, Chetan B. Jawale3, Akshay V. Yewate4, Netra Lokhande5
1Pratik Shiva Meshram, Student, Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India.
2Dhanashree Keshao Parate, Student, Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India.
3Chetan Bhairu Jawale, Student, Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India.
4Akshay Vyankat Yewate, Student, Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India.
5Dr. Netra Lokhande, Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India.
Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 185-189 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3363079220/2020©BEIESP | DOI: 10.35940/ijrte.B3363.079220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Dental radiographs do a great deal of work on the evidence of criminal classification. Science deontology is used in crimes that deal with the evidence of a person’s separation related to dental exposure. Due to the advances in data design and the need to evaluate more cases by legal professionals, it is important to use a human evidence framework. Dental radiographs can be classified as biometric if there are no alternatives to body biometrics, for example, palm, finger, iris, face, leg print, and so on. The human body seen using dental radiographs is best under certain conditions when there are no biometric alternatives because the teeth and bones are treated like skin tissues and tissues found in the human body.
Keywords: CNN, Dental Radiographs, Ho G, KNN.