A novel recognition method for laser active lighting system based on contour torque features and bag of features (BoF) is proposed. The concept of torque is introduced and a multi- scale contour torque feature region detector and a contour torque local invariant feature descriptor are proposed. The multi- scale contour torque feature region detector can extract the smallest feature region that contains the whole contours. The contour torque local invariant features can commendably represent the size, position, shape regularly of the contours, and they are also invariant to image transformation. What′ s more, the features are efficiently to compute. The contour torque local invariant features of an image with BoF algorithm is added up to generate normalized feature histogram, which is then input into the trained support vector machine (SVM) for recognition. The experimental results indicate that compared with existing laser active lighting recognition algorithm based on Hu moment and BP neural network, the recognition rate is increased by the proposed method by 7.33% in rotation transform and 19.08% in affine transform, respectively.