摘要
A new method for synthetic aperture radar (SAR) target recognition is proposed. This method is accomplished via the combination of active contour without edges, Hu invariant moments and support vector machine (SVM) classifier. Image segmentation is performed by using active contour without edges. Then seven Hu moments are extracted and normalized as feature vectors. Finally, the SVM classifier is employed for data training and testing by means of MSTAR SAR images. To verify the performance of the proposed method, the traditional active contour (snakes) is used for comparison. The simulation results confirm the feasibility and accuracy of the proposed method in SAR target recognition. © 2017 Beijing Institute of Aerospace Information.
A new method for synthetic aperture radar (SAR) target recognition is proposed. This method is accomplished via the combination of active contour without edges, Hu invariant moments and support vector machine (SVM) classifier. Image segmentation is performed by using active contour without edges. Then seven Hu moments are extracted and normalized as feature vectors. Finally, the SVM classifier is employed for data training and testing by means of MSTAR SAR images. To verify the performance of the proposed method, the traditional active contour (snakes) is used for comparison. The simulation results confirm the feasibility and accuracy of the proposed method in SAR target recognition. © 2017 Beijing Institute of Aerospace Information.
基金
supported by the National Natural Science Foundation of China(41306188
61372004)
the Fundamental Research Funds for the Central Universities
