TY - GEN
T1 - Fusion of global and local features using KCCA for Automatic Target Recognition
AU - Zhao, Jiong
AU - Fan, Yangyu
AU - Fan, Weitao
PY - 2009
Y1 - 2009
N2 - Based on the ideas of feature fusion and Kernel Canonical Correlation Analysis (KCCA), a novel framework for fusing global and local features on Automatic Target Recognition (ATR) algorithm is proposed. Firstly, the feature fusion method based on KCCA is established, then pseudo Zernike moments and Scale Invariant Feature Transform (SIFT) are extracted as global features and local features. K-means algorithm is applied to normalize the local features to obtain the same form as global features. After the fusion of two features, one-against-all Support Vector Machine (SVM) is employed as classifier for the Multi-class target recognition. Theoretical analysis and experiments on aircraft images results show that KCCA features fusion representations significantly outperform CCA fusion method and single feature approach. Feature fusion of global features and local features based on target image for recognition are proved to be a promising strategy in object recognition field.
AB - Based on the ideas of feature fusion and Kernel Canonical Correlation Analysis (KCCA), a novel framework for fusing global and local features on Automatic Target Recognition (ATR) algorithm is proposed. Firstly, the feature fusion method based on KCCA is established, then pseudo Zernike moments and Scale Invariant Feature Transform (SIFT) are extracted as global features and local features. K-means algorithm is applied to normalize the local features to obtain the same form as global features. After the fusion of two features, one-against-all Support Vector Machine (SVM) is employed as classifier for the Multi-class target recognition. Theoretical analysis and experiments on aircraft images results show that KCCA features fusion representations significantly outperform CCA fusion method and single feature approach. Feature fusion of global features and local features based on target image for recognition are proved to be a promising strategy in object recognition field.
KW - Automatic Target Recognition
KW - Feature fusion
KW - Kernel canonical correlation analysis
KW - Support vector machine
UR - http://www.scopus.com/inward/record.url?scp=77952261489&partnerID=8YFLogxK
U2 - 10.1109/ICIG.2009.149
DO - 10.1109/ICIG.2009.149
M3 - 会议稿件
AN - SCOPUS:77952261489
SN - 9780769538839
T3 - Proceedings of the 5th International Conference on Image and Graphics, ICIG 2009
SP - 958
EP - 962
BT - Proceedings of the 5th International Conference on Image and Graphics, ICIG 2009
PB - IEEE Computer Society
T2 - 5th International Conference on Image and Graphics, ICIG 2009
Y2 - 20 September 2009 through 23 September 2009
ER -