Fast contour torque features based recognition in laser active imaging system

Recent years laser active imaging system are widely used as a useful detection artifice. While many denoising and enhancing algorithms have been proposed, target recognition in laser active imaging is still a new domain that few researches have been done. Classical recognition methods often break done due to the characteristic of laser active imaging. In this paper we present a novel target recognition method based on fast contour torque features (FCTF). The proposed fast contour torque features contain abundant information of the target, such as the size, position, darkness and shape regularly of the contours. Meanwhile the features are invariant to rotation, scaling and affine transform, and can be computed efficiently.We first extract feature regions by MSER algorithm, and transform them into circular areas, so the regions are invariant to affine transform. Then local invariant features of the feature regions were extracted by fast contour torque feature descriptor and we input into the trained SVM classifier for identify. Comprehensive experiments show that our approach achieves higher recognition rate in rotation and affine transformation as state-of-art method, and meet the real-time requirement in laser active imaging.