论文信息 - A Novel Feature Fusion Approach Based on Blocking and Its Application in Image Recognition

A Novel Feature Fusion Approach Based on Blocking and Its Application in Image Recognition

According to the idea of canonical correlation analysis, a block-based method for feature extraction is proposed. The main process can be explained as follows: extract two groups of feature vectors from different blocks which belong to the same pattern; and then extract their canonical correlation features to form more effective discriminant vectors for recognition. To test this new approach, the experiment is performed on ORL face database and it shows that the recognition rate is higher than that of algorithm adopting single feature.

[1] D.-S. Huang,et al. Radial Basis Probabilistic Neural Networks: Model and Application , 1999, Int. J. Pattern Recognit. Artif. Intell..

[2] De-Shuang Huang. Application of Generalized Radial Basis Function Networks to Recognition of Radar Targets , 1999, Int. J. Pattern Recognit. Artif. Intell..

[3] David Weenink,et al. CANONICAL CORRELATION ANALYSIS , 2003 .

[4] H. Hotelling. Relations Between Two Sets of Variates , 1936 .

[5] Alejandro F. Frangi,et al. Two-dimensional PCA: a new approach to appearance-based face representation and recognition , 2004 .

[6] De-Shuang Huang,et al. Linear and Nonlinear Feedforward Neural Network Classifiers: A Comprehensive Understanding , 1999 .

[7] Yan Liu,et al. A new method of feature fusion and its application in image recognition , 2005, Pattern Recognit..

[8] P. Green,et al. Analyzing multivariate data , 1978 .

[9] Zhang Hong-mei. Singular value decomposition-based approach for face recognition , 2004 .