We propose a computer aided detection (CAD) system for the detection and classification of suspicious regions in mammographic images. This system combines a dimensionality reduction module (using principal component analysis), a feature extraction module (using independent component analysis), and a feature subset selection module (using rough set model). Rough set model is used to reduce the e...

in the present study, quantitative relationships between molecular structure and anti-tubercular activity of some 5-methyl/trifluoromethoxy-1 h -indole-2,3-dione-3-thiosemicarbazone derivatives were discovered. the detailed application of an efficient linear method and principal component regression (pcr) for the evaluation of quantitative structure activity relationships of the studied compound...

Identity verification using face information is a challenging research area that was very active recently, mainly because of its natural and non intrusive interaction with the authentication system. Principal Component Analysis (PCA) is a typical face based method which considers face as global feature. In this paper, we propose a new face based authentication approach based on the use of face ...

Classification is a very important task for scene interpretation and other applications of multispectral images. Feature extraction is a key step for classification. By extracting more nonlinear features than corresponding number of linear features in original feature space, classification accuracy for multispectral images can be improved greatly. Therefore, in this paper, an approach based on ...

t is the purpose of this paper to contribute to the discussion initiated bywachter about the parallelism between principal component (pc) and atypological grade of membership (gom) analysis. the author testedempirically the close relationship between both analysis in a lowdimensional framework comprising up to nine dichotomous variables and twotypologies. our contribution to the subject is also...

Face Recognition (FR) has a wide range of applications, such as face-based video indexing, human-computer interaction, and surveillance system. The recognition rate can reach more than 90% with the frontal face, while dealing with faces are oriented or rotated, the accuracy just achieves 40% or 50%. Hence, an algorithm is proposed in this paper to deal with the problem. The face pose is first d...