1. An image clustering method, comprising: extracting a Global Scene Semantic (GIST) feature of a first image and a GIST feature of a second image, wherein the first image is a first advertising image comprised in a first advertising order and the second image is a second advertising image comprised in a second advertising order; obtaining an image fingerprint of the first image based on the GIST feature of the first image, and obtaining an image fingerprint of the second image based on the GIST feature of the second image, wherein the obtaining an image fingerprint of the first image based on the GIST feature of the first image and obtaining an image fingerprint of the second image based on the GIST feature of the second image comprises: obtaining the image fingerprint of the first advertising image, based on the GIST feature of the first advertising image and a SimHash algorithm in a Local Sensitive Hashing (LSH) algorithm, and obtaining the image fingerprint of the second advertising image, based on the GIST feature of the second advertising image and the SimHash algorithm in the LSH algorithm; calculating a similarity between the first image and the second image, based on the image fingerprint of the first image and the image fingerprint of the second image; and determining whether the similarity between the first image and the second image is larger than a predetermined similarity threshold, and classifying the first image and the second image as a same category of image in a case that the similarity between the first image and the second image is larger than the predetermined similarity threshold.