Algebraic feature extraction for image recognition

Ke Liu, Ying-Jiang Liu, Yong-Qing Cheng, Jingyu Yang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993

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.

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