Fuzzy Face Recognition Based On Skin Texture Fusion Model
Yogish Naik G.R.1, Prabhakar C.J.2, Arun Kumar H.D.3, Thontadari C.4
1Yogish Naik G.R, Computer Science and MCA Department, Kuvempu University, Karnataka, India.
2Prabhakar C.J, Computer Science and MCA Department, Kuvempu University, Karnataka, India.
3Arun Kumar H.D, Computer Science and MCA Department, Kuvempu University, Karnataka. Thontadari C, Computer Science and MCA Department, Kuvempu University, Karnataka, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 541-544 | Volume-8 Issue-6, August 2019. | Retrieval Number: E7315068519/2019©BEIESP | DOI: 10.35940/ijeat.E7315.088619
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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: Facerecognition is a research are in computer vision and pattern recognition because of its importance in real applications like human machine interaction, video surveillance, and security systems. Here we have proposed a fuzzy model for robust facerecognition using gradient and texture information. Initially, the local binary pattern (LBP) and histogram of oriented gradients (HOG) feature of face skin from the original images are extracted. These two features are used for the development of our fuzzy model. For the analysis of faces, a content-based similarity measure is developed and used for data analysis of trained face model and test face model. The proposed algorithm is experimented on LFW, AR, and ORL face databases. The proposed fuzzy face fusion model approach shows that our proposed method is having good recognition rate compared to facerecognition methods developed recently.
Keywords: Face Recognitionl, Histogram of Oriented Gradients, Binary Pattern, LBP.