The work aims to solve the problem of low perceptual robustness and forgery detection ability of Hash algorithm and propose the compact image Hash algorithm based on the feature compression mechanism and local binary pattern (LBP) in the neighborhood space. Firstly, the 2D liner interpolation was introduced to preprocess the input image and such image was changed into a secondary image with the Ring segmentation technology. Then, the Gabor filter technique was used to filter the image. LBP operator in the neighborhood space was designed based on LBP by considering the color feature and the intrinsic spatial relationship of image for extracting the feature of the filter image. The feature compression quantization rule was constructed to output the compact Hash binary array. The Logistic mapping was iterated to output the random sequence. The key stream was generated by quantifying each sequence value to design the segment diffusion model by constructing the dynamic engine, so as to realize the encryption of compact Hash sequence and obtain the image Hash. Finally, the Hamming distance between the original Hash sequence and the Hash sequence to be detected was calculated, and the security authentication of the image information was realized. The test results showed that, compared with the existing Hash generation mechanism, the proposed algorithm was more compact and more robust to rotation, gamma correction and other tampering operations. The proposed Hash technique has higher security and better value in the fields of packaging icon retrieval and information detection, etc.