26 March 1993 Algebraic feature extraction for image recognition
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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.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ke Liu, Ke Liu, Ying-Jiang Liu, Ying-Jiang Liu, Yong-Qing Cheng, Yong-Qing Cheng, Jingyu Yang, 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); doi: 10.1117/12.142204; https://doi.org/10.1117/12.142204


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