Face Recognition using Discrete Haar Wavelet Transforms
Meenu Kumari1, Anil Kumar2, Manish Saxena3
1Meenu Kumari, Department of Physics, IFTM University, Moradabad-244001, India.
2Anil Kumar, Department of Physics, Hindu College, Moradabad-244001, India.
3Manish Saxena, Department of Physics, Moradabad Institute of Technology, Moradabad -244001, India.
Manuscript received on 03 August 2019. | Revised Manuscript received on 08 August 2019. | Manuscript published on 30 September 2019. | PP: 6600-6604 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5608098319/2019©BEIESP | DOI: 10.35940/ijrte.C5608.098319
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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: Wavelet transform is being applied as an important analyzing tool in signal and image processing because it provides better signal representations with less computation time because of property of multiresolution analysis. An analogue image is transformed into a discrete image in a space through a sampling process. The wavelet transforms and analysis of discrete image are performed using Haar wavelet, level-2. Through analyzing and comparing different patterns, one or more persons are identified in the face recognition process. It is accomplished by using correlation coefficient and Euclidean distance of scaling coefficients of wavelet transformed images. In the face recognition the typically facial features are extracted and compared to a database for finding the best match. Matching of features is performed between test image and stored database images.
Keywords: Approximation, Correlation, Euclidean, Face, Image, Wavelet.
Scope of the Article: Image Processing and Pattern Recognition