Proposed A New Multidimensional Face Recognition For Surgically Altered Faces in Security Surveillance
Dimple Chawla1, Munesh Chandra Trivedi2
1Dimple Chawla, Research Scholar, PAHER University, Udaipur (Rajasthan), India.
2Dr. Munesh Chandra Trivedi, Dean (Academics), Rajkiya Engineering College, Azamgarh (Uttar Pradesh), India.
Manuscript received on 18 August 2019 | Revised Manuscript received on 29 August 2019 | Manuscript Published on 06 September 2019 | PP: 1021-1026 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F11950886S19/19©BEIESP | DOI: 10.35940/ijeat.F1195.0886S19
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Abstract: From previously carried out review results, authors have proposed a new multidimensional face recognition approach and applied on the sample database of sensitive medical images. The basic idea is to differentiate an individual’s identity with its own core features extracted from local or global plastic surgery. Features are being highlighted to match pre-topost or post-to-pre surgery face images. The procedure may affect different face recognition algorithms working on linear or nonliner variations approach and that’s what multidimensional approach is meant. Hence it proves that the performance of verified rank accuracy ratio has increased in face recognition for security surveillance.
Keywords: Face Recognition, Feature Extractors Algorithm, Principal Component Analysis (PCA), Independent Component Analysis (ICA), Local Binary Pattern (LBP), Fisher Discriminate Analysis (FDA), Local Feature Analysis (LFA).
Scope of the Article: Pattern Recognition