Target Recognition in laser active imaging based on fast contour torque features

Due to the characteristic of images in laser active imaging, a novel target recognition method based on fast contour torque features(FCTF) is proposed. The concept of torque is introduced into target recognition. The proposed fast contour torque features contain abundant information such as the size, position, shape regularly of the contours and darkness of the target, which are as well invariant to rotation and scaling. Meanwhile the fast calculation method greatly improves the computational efficiency. Firstly feature regions are detected using Maximally Stable Extremal Regions(MSER) algorithm, and transformed into circular areas. Then local invariant features of the feature regions are extracted by fast contour torque feature descriptor. At last the features are input into the trained Suppor Vector Machine(SVM) classifier for identification. The experimental results indicate that compared with the existing laser active imaging recognition algorithms, the proposed method acquires higher recognition rate in rotation and affine transformation, and the average computing time of single frame is 9.68 ms, which meet the real-time requirement in laser active imaging.