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Proceedings Paper

Human face recognition by Euclidean distance and neural network
Author(s): Chomtip Pornpanomchai; Chittrapol Inkuna
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Paper Abstract

The idea of this project development is to improve the concept of human face recognition that has been studied in order to apply it for a more precise and effective recognition of human faces, and offered an alternative to agencies with respect to their access-departure control system. To accomplish this, a technique of calculation of distances between face features, including efficient face recognition though a neural network, is used. The system uses a technique of image processing consisting of 3 major processes: 1) preprocessing or preparation of images, 2) feature extraction from images of eyes, ears, nose and mouth, used for a calculation of Euclidean distances between each organ; and 3) face recognition using a neural network method. Based on the experimental results from reading image of a total of 200 images from 100 human faces, the system can correctly recognize 96 % with average access time of 3.304 sec per image.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 754603 (26 February 2010); doi: 10.1117/12.852248
Show Author Affiliations
Chomtip Pornpanomchai, Mahidol Univ. (Thailand)
Chittrapol Inkuna, Mahidol Univ. (Thailand)


Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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