JOURNAL ARTICLE

<title>Algebraic feature extraction for image recognition</title>

Ke LiuYing-Jiang LiuYong-Qing ChengJingyu Yang

Year: 1993 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 1819 Pages: 225-231   Publisher: SPIE

Abstract

A novel algebraic feature extraction method for image recognition is presented. For the training image samples, a set of optimal discriminant projection vectors are calculated according to a generalized Fisher criterion function. On the basis of the optimal discriminant projection vector, the algebraic feature vectors of an image can be extracted by projecting the image onto all optimal discriminant projection vectors. Experimental results shows that the algebraic features extracted by the presented method have good recognition performance.

Keywords:
Discriminant Pattern recognition (psychology) Projection (relational algebra) Artificial intelligence Feature extraction Linear discriminant analysis Feature vector Feature (linguistics) Computer science Algebraic number Image (mathematics) Set (abstract data type) Computer vision Mathematics Algorithm

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FWCI (Field Weighted Citation Impact)
11
Refs
0.17
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Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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