Semi-supervised ladder network-based image hash retrieval method

Abstract

The invention discloses a semi-supervised ladder network-based image hash retrieval method. The method comprises the steps of selecting images in a database and to-be-retrieved images to perform preprocessing; inputting the preprocessed images to a trained semi-supervised ladder network for performing feature extraction, wherein the semi-supervised ladder network comprises an unsupervised ladder network and a convolutional neural network, the convolutional neural network comprises a convolutional layer, a pooling layer, a full connection layer and a hidden layer connected in sequence, and thehidden layer performs hash expression on image features by utilizing a hash activation function to obtain feature codes; comparing the feature codes to determine a group which the to-be-retrieved images belong to; and calculating distances between the to-be-retrieved images and eigenvectors of the images in the group, and outputting N images with shortest distances. The problems of low accuracy, relatively long algorithm time and sample tagging deficiency in an image retrieval process are solved.

Description

technical field [0001] The invention belongs to the field of image retrieval, and in particular relates to an image hash retrieval method based on a semi-supervised ladder network. Background technique [0002] With the enhancement of hardware computing power, image retrieval has been more widely and deeply applied in various practical problems such as search engines, e-commerce, and video pedestrian re-detection. Due to the wide range of sources of images on the Internet, the amount of image data is extremely large, so it is impossible to give the best description for each image. For data processing, it is equivalent to more sample data, but the amount of labeled data is relatively small. . In this case, descriptions of similar images are beneficial for image understanding. Therefore, image search can solve this problem, that is, as long as there is an image with a high similarity to the image in the existing database, the image can be understood with the description of t...

AI Technical Summary

Problems solved by technology

[0007] In order to solve the technical problems raised by the above-mentioned background technology, the present invention aims to provide an image hash retrieval method based on a semi-supervised ladder network, which solves the problems of low accuracy, long time-consuming algorithm and insufficient sample labeling in the image retrieval process

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