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International Journal of Innovation and Scientific Research
ISSN: 2351-8014
 
 
Friday 29 March 2024

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FACE RECOGNITION USING HAAR WAVELET TRANSFORM


Volume 25, Issue 2, July 2016, Pages 399–404

 FACE RECOGNITION USING HAAR WAVELET TRANSFORM

R. Karpagam1, P. Subbalakshmi2, and C. Balasubramanian3

1 Dept.of CSE, P.S.R. Rcollege of Engg For Women, Sivakasi, India
2 Asst.Prof Dept Of CSE, P.S.R. Rcollege of Engg For Women, Sivakasi, India
3 Prof. and head of Department of Computer Science and Engineering, P.S.R.Renasamy College of Engineering for women, Sivakasi, Tamilnadu, India

Original language: English

Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


In image processing is to identify the human faces in difficult to recognizing image analysis which has each day most applications. The main idea in the building of the detector is a learning classification built on ada-boost. The families of simple classifiers contain simple rectangular wavelets which are reminiscent of the Haar basis. Their ease and a new image representation called Integral Image allow a very quick computing of these Haar-like features. An assembly in cascade is introduced in order to reject quickly the easy to classify background regions and focus on the inflexible to classify windows. The structure of the SVM classifier allows a real-time implementation of the indicator. Some results on real world examples are presented. The detector yields good detection rates with frontal faces then the process can be easily adapted to other object detection tasks by changing the contents of the training dataset.

Author Keywords: Face recognition, Haar Wavelet Transform.


How to Cite this Article


R. Karpagam, P. Subbalakshmi, and C. Balasubramanian, “FACE RECOGNITION USING HAAR WAVELET TRANSFORM,” International Journal of Innovation and Scientific Research, vol. 25, no. 2, pp. 399–404, July 2016.