Human face recognition by Euclidean distance and neural network

Chomtip Pornpanomchai; Chittrapol Inkuna

doi:10.1117/12.852248

26 February 2010 Human face recognition by Euclidean distance and neural network

Chomtip Pornpanomchai, Chittrapol Inkuna

Proceedings Volume 7546, Second International Conference on Digital Image Processing; 754603 (2010) https://doi.org/10.1117/12.852248
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore

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.

Citation Download Citation

Chomtip Pornpanomchai and Chittrapol Inkuna "Human face recognition by Euclidean distance and neural network", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 754603 (26 February 2010); https://doi.org/10.1117/12.852248

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