Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algebraic feature extraction of image for recognition
Pattern Recognition
A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Orthogonal Moment Features for Use With Parametric and Non-Parametric Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of Handwritten Numerals Using Gabor Features
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Journal of Cognitive Neuroscience
Robust coding schemes for indexing and retrieval from large face databases
IEEE Transactions on Image Processing
A shape- and texture-based enhanced Fisher classifier for face recognition
IEEE Transactions on Image Processing
Improvements on CCA model with application to face recognition
Intelligent information processing II
Locality preserving CCA with applications to data visualization and pose estimation
Image and Vision Computing
Multiple feature fusion by subspace learning
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
A New Canonical Correlation Analysis Algorithm with Local Discrimination
Neural Processing Letters
An indirect and efficient approach for solving uncorrelated optimal discriminant vectors
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
A multilevel information fusion approach for visual quality inspection
Information Fusion
A novel feature fusion approach based on blocking and its application in image recognition
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Feature-level fusion of fingerprint and finger-vein for personal identification
Pattern Recognition Letters
Analysis of Correlation Based Dimension Reduction Methods
International Journal of Applied Mathematics and Computer Science - Issues in Advanced Control and Diagnosis
Face recognition based on generalized canonical correlation analysis
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Weak metric learning for feature fusion towards perception-inspired object recognition
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Ultrasonic liver tissue characterization by feature fusion
Expert Systems with Applications: An International Journal
Face verification with feature fusion of Gabor based and curvelet based representations
Multimedia Tools and Applications
Local CCA alignment and its applications
Neurocomputing
Fusion and inference from multiple data sources in a commensurate space
Statistical Analysis and Data Mining
Neighborhood Correlation Analysis for Semi-paired Two-View Data
Neural Processing Letters
Video key frame extraction through dynamic Delaunay clustering with a structural constraint
Journal of Visual Communication and Image Representation
Multi-resolution feature fusion for face recognition
Pattern Recognition
Face Recognition with Integrating Multiple Cues
Journal of Signal Processing Systems
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A new method of feature extraction, based on feature fusion, is proposed in this paper according to the idea of canonical correlation analysis (CCA). At first, the theory framework of CCA used in pattern recognition and its reasonable description are discussed. The process can be explained as follows: extract two groups of feature vectors with the same pattern; establish the correlation criterion function between the two groups of feature vectors; and extract their canonical correlation features to form effective discriminant vector for recognition. Then, the problem of canonical projection vectors is solved when two total scatter matrixes are singular, such that it fits for the case of high-dimensional space and small sample size, in this sense, the applicable range of CCA is extended. At last, the inherent essence of this method used in recognition is analyzed further in theory. Experimental results on Concordia University CENPARMI database of handwritten Arabic numerals and Yale face database show that recognition rate is far higher than that of the algorithm adopting single feature or the existing fusion algorithm.