Feature Based Face Recognition using Machine Learning Techniques
Bhanushree K. J.1, Meenavathi M. B.2
1Bhanushree K. J.*, Department of computer science, Bangalore institute of technology, Bangalore, India.
2Meenavathi M. B.*, Department of electronics and instrumentation engineering, Bangalore institute of technology, Bangalore, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1313-1317 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7497038620/2020©BEIESP | DOI: 10.35940/ijrte.F7497.038620
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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: Human Face has Numerous unique Features to Distinguish between each other. Face can Identified by distinguishing between face and non-face followed by Identification. Traditionally face recognition uses distinct features Comparison to Identify the Faces which is Complex for larger databases and ambiguous in many scenarios. To improve the accuracy and Scalability Proposed method uses machine learning based Haar Cascade technique for face detection and convolutional neural network is used for feature extraction followed by classification using Euclidean distance and cosine transformation to recognize the face. The results demonstrate the work is performed well in recognizing the face efficiently with different variations.
Keywords: Feature Extraction. Discrete Cosine Transformation; Face Recognition Euclidean Distance; Face Detection.
Scope of the Article: Machine Learning.