Algebraic feature extraction for image recognition

Ke Liu; Ying-Jiang Liu; Yong-Qing Cheng; Jingyu Yang

doi:10.1117/12.142204

26 March 1993 Algebraic feature extraction for image recognition

Ke Liu, Ying-Jiang Liu, Yong-Qing Cheng, Jingyu Yang

Proceedings Volume 1819, Digital Image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences II; (1993) https://doi.org/10.1117/12.142204
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

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.

Citation Download Citation

Ke Liu, Ying-Jiang Liu, Yong-Qing Cheng, and Jingyu Yang "Algebraic feature extraction for image recognition", Proc. SPIE 1819, Digital Image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences II, (26 March 1993); https://doi.org/10.1117/12.142204

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