A novel target recognition method for laser active imaging based on a kind of local invariant feature named fast retina key point (FREAK) is proposed, which could be used when moment, geometry and contour features of target are difficult to extract. A feature point detection method called difference of features from accelerated segment test (FAST-Difference) is proposed. It combines features from accelerated segment test (FAST) with difference of Gaussian (DoG), which can rapidly extract feature points that are robust for a variety of transformation. FREAK descriptor is used to generate the feature vectors and cascading matching method is used to complete the fast matching for feature vectors. The proposed method has characteristics similar to those of human vision. In the feature point detection stage, the FAST-Difference method uses DoG for multi-scale detection. In the feature vector description stage, FREAK descriptor has similar topology structure with human retina. In the feature vector matching stage, cascading matching method imitates saccade search of human retina. Experimental result indicates that the proposed method can quickly and effectively recognize the partly-illuminated tower-like target in laser active imaging and satisfy the real-time requirement of the recognition system.