International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 163 - Issue 4 |
Published: Apr 2017 |
Authors: Ranjana Sikarwar, Pradeep Yadav |
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Ranjana Sikarwar, Pradeep Yadav . An Approach to Face Detection and Feature Extraction using Canny Method. International Journal of Computer Applications. 163, 4 (Apr 2017), 1-5. DOI=10.5120/ijca2017913492
@article{ 10.5120/ijca2017913492, author = { Ranjana Sikarwar,Pradeep Yadav }, title = { An Approach to Face Detection and Feature Extraction using Canny Method }, journal = { International Journal of Computer Applications }, year = { 2017 }, volume = { 163 }, number = { 4 }, pages = { 1-5 }, doi = { 10.5120/ijca2017913492 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2017 %A Ranjana Sikarwar %A Pradeep Yadav %T An Approach to Face Detection and Feature Extraction using Canny Method%T %J International Journal of Computer Applications %V 163 %N 4 %P 1-5 %R 10.5120/ijca2017913492 %I Foundation of Computer Science (FCS), NY, USA
This paper presents a hybrid approach to face detection and feature extraction. The remarkable advancement in technology has enhanced the use of more accurate and precise methods to detect faces. This paper presents a combination of three well known algorithms Viola- Jones face detection framework, Neural Networks and Canny edge detection method to detect face in static images. The proposed work emphasizes on the face detection and identification using Viola-Jones algorithm which is a real time face detection system. Neural Networks will be used as a classifier between faces and non-faces. Canny edge detection method is an efficient method for detecting boundaries on a face in this proposed work. The Canny edge detector is primarily useful to locate sharp intensity changes and to find object boundaries in an image.