Biometric Validation using Back-Propagation Neural Network
A.Annamalai Giri1, A.Gayathri2, E.Mohan3

1Dr.A.Annamalai Giri*, Professor, Department of Computer Science and Engineering, Marri Laxman Reddy Institute of Technology and Management, Dundigal, Hyderabad, India.
2A.Gayathri, Research Scholar, Department of Electrical and Electronics, Annamalai University, Tamilnadu, India.
2Dr. E.Mohan, Professor, Department of Computer Science and Engineering, Lord Venkateshwaraa Engineering College, Kanchipuram, Tamilnadu, India.

Manuscript received on April 30, 2020. | Revised Manuscript received on May 06, 2020. | Manuscript published on May 30, 2020. | PP: 1865-1867 | Volume-9 Issue-1, May 2020. | Retrieval Number: A2129059120/2020©BEIESP | DOI: 10.35940/ijrte.A2129.059120
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: The aim of this paper is to affirm particular persons as pointed out with aid of their claws. We come up with a method to get rid of Finger Texture (FT) feature of the twain finger depiction (middle, annular) from a depressed intention using appropriate LBP strategy for fist image. The application of Inner-Knuckle-Print (IKP) in biometric authentication is the prospective recognition taskk. The exclusive attribute of the IKP provide us the prerequisite for significant validation. In the interim IKP filtering transform, the copy of the picture generated by the scanner will be partly exclusive. The article introduce ANN for adequately regulate strategy to IKP authorization. By applying the Back-Propagation technique, the method harmonize IKP and disclose them to a unique proficient client.
Keywords: IKP, Feature extraction, LMBP, GLCM, BPN,SVM.
Scope of the Article: Neural Network