Unsupervised image retrieval method based on hash coding

Abstract

The invention provides an unsupervised image retrieval method based on hash coding. The method comprises the steps of processing videos to obtain image library data; then training a classifier on an image library and selecting out first half of good-quality images by use of the classifier on a training set; retraining a new classifier by use of the selected-out images and performing screening on the image library by use of the new classifier; training the classifier by use of the images selected out from the image library again; and carrying out operations in the same manner, thereby obtaining a retrieval model by alternate iterative training of the classifier.

Description

technical field [0001] The invention relates to the field of digital image processing, and more specifically, to an unsupervised image retrieval method based on hash coding. Background technique [0002] In recent years, with the development of computer network, multimedia technology and digital image equipment, digital image technology has penetrated into all aspects of society, such as mass media, military aerospace, family life, etc. In this context, image databases are becoming more and more large-scale, and how to quickly retrieve images in huge databases has become an urgent and critical issue. The commonly used technology for early image retrieval is semantic labeling, but there is no clear standard for semantic labeling, that is, different people have different understandings of the same picture and choose different semantic labels. Therefore, using semantic tags as retrieval criteria cannot achieve ideal results. In addition, as the scale of the database expands, ...

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Problems solved by technology

Therefore, using semantic tags as retrieval criteria cannot achieve ideal results.

In addition, as the scale of the database expands, it becomes more and more complicated to set semantic tags for all pictures. People need a new solution to free workers from the tedious work of setting tags.

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