Cross-modal retrieval of large-scale images in social media based on spatial distribution entropy

In order to improve the cross-modal retrieval accuracy of large-scale social media images, a cross-modal retrieval method for large-scale social media images based on spatial distribution entropy is proposed. First, extract the information features of the colour and texture of the image. Then, use the image cross-modal retrieval method based on the spatial distribution entropy to calculate the spatial distribution entropy of the colour information and texture information features in the image. Finally, use the Euclidean distance to judge the space between social media images. The matching degree of the distribution entropy, according to the matching degree, is used to judge whether the image cross-modal retrieval is successful or not. The experimental results verify that the proposed method can implement comprehensive retrieval according to the specific characteristics of the retrieved images, and the matching degree of image retrieval is greater than 95%, and the retrieval accuracy is high.