Compact representation of the facial images for identification in a parallel-hierarchical network

Yuri F. Kutaev; Leonid I. Timchenko; Alexander A. Gertsiy; Lubov V. Zahoruiko

doi:10.1117/12.326956

6 October 1998 Compact representation of the facial images for identification in a parallel-hierarchical network

Yuri F. Kutaev, Leonid I. Timchenko, Alexander A. Gertsiy, Lubov V. Zahoruiko

Proceedings Volume 3521, Machine Vision Systems for Inspection and Metrology VII; (1998) https://doi.org/10.1117/12.326956
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

The work offers the methods for invariant representation of images against a variety of distorting factors including 2D and 3D rotation, changes in brightness, contrast and scale. The problems of preliminary image processing based on the method of generalized Q-transformation are being solved. The calculating algorithms based on the methodology of dichotomous balance of the images being prepared have been used for the classification of human facial images. It also deals with the procedure of recursive contour preparation consisting of step-by-step preparation of differences among the pixels of grey-scale image and formation of positive, negative and zero preparations. Thus at the first step the contour preparation is effected for the first differences, at the second step, for the second differences, and so on, with a step-by-step definition of the criterial function of distribution of binarized preparations. So it is possible to identify objects in different lighting conditions which simplifies the implementation of similar approaches. This relative simplicity of this method extends the range of its possible application for recognition purposes and for its implementation in the parallel-hierarchical network in particular.

Citation Download Citation

Yuri F. Kutaev, Leonid I. Timchenko, Alexander A. Gertsiy, and Lubov V. Zahoruiko "Compact representation of the facial images for identification in a parallel-hierarchical network", Proc. SPIE 3521, Machine Vision Systems for Inspection and Metrology VII, (6 October 1998); https://doi.org/10.1117/12.326956

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