Picture retrieval method and system

Abstract

The invention provides a picture retrieval method and system and relates to the technical field of picture retrieval. In the embodiment, a picture data set is first built; feature data of each picture is extracted and processed to achieve a feature data matrix; then a category matrix and a category-attribute matrix are built according to category information where the picture belongs to; the feature data matrix is divided into a training matrix and a test matrix and further a Hash transferring function is gained; the training matrix and the test matrix are encoded via the Hash transferring function; a preset number of pictures is extracted from the training encoding matrix and the test encoding matrix to form a retrieval base; at last, a picture is selected from the test encoding matrix; a Hamming distance between a Hash code of the picture and a Hash code of a picture in the retrieval base is calculated; and retrieval results are orderly output according to the Hamming distance. The embodiment can effectively improve picture retrieval efficiency and reduce picture retrieval cost.

Description

technical field [0001] The present invention relates to the technical field of picture retrieval, in particular to a picture retrieval method and system. Background technique [0002] With the development of cloud computing, Internet of Things, mobile phones, social media and other information technologies, the data on the Internet is growing explosively, and the era of big data has arrived. In the era of big data, how to perform fast image retrieval is the focus of people's attention. Among them, hash learning saves storage space and speeds up query by learning the binary code representation of pictures, and has been widely studied in picture similarity retrieval. According to the inventor's research, traditional hash learning requires people to pre-label a large number of pictures to be encoded for pre-training of the hash learning algorithm. However, in the era of big data, with the continuous emergence of new data, expensive manual labeling And the time-consuming pre-t...

AI Technical Summary

Problems solved by technology

According to the inventor's research, traditional hash learning requires people to pre-label a large number of pictures to be encoded for pre-training of the hash learning algorithm. However, in the era of big data, with the continuous emergence of new data, expensive manual labeling And the time-consuming pre-training process hinders the application of hash learning algorithm in the actual image retrieval process

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