REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION

Face recognition is one of the intensive areas of research in computer vision and pattern recognition but many of which are focused on recognition of faces under varying facial expressions and pose variation. A constrained optical flow algorithm discussed in this paper, recognizes facial images invo...

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Main Authors: D. Sathish Kumar, S. Joshua Kumaresan
Format: Article
Language:English
Published: ICT Academy of Tamil Nadu 2013-05-01
Series:ICTACT Journal on Image and Video Processing
Subjects:
Online Access:http://ictactjournals.in/paper/Paper6_626_629.pdf
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spelling doaj-3b4bd660d1304d89a67b5030988267192020-11-25T01:35:46ZengICT Academy of Tamil NaduICTACT Journal on Image and Video Processing0976-90990976-91022013-05-0134626629REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATIOND. Sathish Kumar0S. Joshua Kumaresan1Department of Electronics and Communication Engineering, RMK Engineering College, IndiaDepartment of Electronics and Communication Engineering, RMK Engineering College, IndiaFace recognition is one of the intensive areas of research in computer vision and pattern recognition but many of which are focused on recognition of faces under varying facial expressions and pose variation. A constrained optical flow algorithm discussed in this paper, recognizes facial images involving various expressions based on motion vector computation. In this paper, an optical flow computation algorithm which computes the frames of varying facial gestures, and integrating with synthesized image in a probabilistic environment has been proposed. Also Histogram Equalization technique has been used to overcome the effect of illuminations while capturing the input data using camera devices. It also enhances the contrast of the image for better processing. The experimental results confirm that the proposed face recognition system is more robust and recognizes the facial images under varying expressions and pose variations more accurately.http://ictactjournals.in/paper/Paper6_626_629.pdfOptical Flow AlgorithmSkin Color SegmentationHistogram EqualizationFeature ExtractionPattern Matching
collection DOAJ
language English
format Article
sources DOAJ
author D. Sathish Kumar
S. Joshua Kumaresan
spellingShingle D. Sathish Kumar
S. Joshua Kumaresan
REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION
ICTACT Journal on Image and Video Processing
Optical Flow Algorithm
Skin Color Segmentation
Histogram Equalization
Feature Extraction
Pattern Matching
author_facet D. Sathish Kumar
S. Joshua Kumaresan
author_sort D. Sathish Kumar
title REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION
title_short REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION
title_full REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION
title_fullStr REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION
title_full_unstemmed REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION
title_sort real-time face recognition based on optical flow and histogram equalization
publisher ICT Academy of Tamil Nadu
series ICTACT Journal on Image and Video Processing
issn 0976-9099
0976-9102
publishDate 2013-05-01
description Face recognition is one of the intensive areas of research in computer vision and pattern recognition but many of which are focused on recognition of faces under varying facial expressions and pose variation. A constrained optical flow algorithm discussed in this paper, recognizes facial images involving various expressions based on motion vector computation. In this paper, an optical flow computation algorithm which computes the frames of varying facial gestures, and integrating with synthesized image in a probabilistic environment has been proposed. Also Histogram Equalization technique has been used to overcome the effect of illuminations while capturing the input data using camera devices. It also enhances the contrast of the image for better processing. The experimental results confirm that the proposed face recognition system is more robust and recognizes the facial images under varying expressions and pose variations more accurately.
topic Optical Flow Algorithm
Skin Color Segmentation
Histogram Equalization
Feature Extraction
Pattern Matching
url http://ictactjournals.in/paper/Paper6_626_629.pdf
work_keys_str_mv AT dsathishkumar realtimefacerecognitionbasedonopticalflowandhistogramequalization
AT sjoshuakumaresan realtimefacerecognitionbasedonopticalflowandhistogramequalization
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