Local Binary Pattern is a Good Descriptor for AI-Generated Image Detection

Advancements in image generation technologies have raised significant concerns about their potential misuse, such as producing misinformation and deepfakes. Therefore, there is an urgent need for effective methods to detect AI-generated images. Recent studies reveal that texture is an important cue for fake image detection since the generator typically correlates the values of nearby pixels and cannot generate as strong texture contrast as real data. However, these methods compute the image texture only by simply summing the residual of four directions. In this paper, we find that Local Binary Pattern (LBP), which is a good texture descriptor, can capture intrinsic forgery clues. To this end, we proposed an LBP-based AI-generated image Detector, named as LBPDbased. To fully leverage the LBP descriptor of images, we also proposed an LBP-guided AI-generated image detector LBPDguided, which combines LBP descriptor with image features by the proposed global refinement module from both spatial and channel perspectives. Extensive experiments validate the effectiveness of the proposed method. It also achieves state-of-the-art results across various evaluation benchmarks.