Picture retrieval method

Abstract

The invention discloses a picture retrieval method. The method comprises the steps of carrying out DCT calculation and DWT calculation on a processed picture to obtain a first group of hash codes, performing DCT calculation and DWT calculation on the rotationally processed pictures at 90 degrees, 180 degrees and 270 degrees to obtain a second group of hash codes, a third group of hash codes and afourth group of hash codes, calculating and constructing an NB+tree based on the four groups of hash codes, combining the NB+tree into a random forest model, and performing picture retrieval by usingthe random forest model. A block DCT and DWT technology is used for constructing a perceptual hash code of a picture, so that the hash code construction process is accelerated; a decision tree is constructed according to the pictures with different rotation angles, so that the picture retrieval accuracy is improved; a normalized B+tree is used for reducing a high-dimensional input vector to one dimension, so that the time complexity is remarkably improved; a random forest model is used, and multiple decisions such as picture rotation, DCT and DWT hash codes are combined to improve the retrieval speed and performance.

Description

technical field [0001] The invention belongs to the technical field of image retrieval, and in particular relates to a method for image retrieval. Background technique [0002] With the rapid development of graphics hardware, computer technology, and Internet technology, large-scale image data has been widely used in various human production activities. perform efficient searches. [0003] The current image retrieval technology is mainly divided into two categories, one is text-based image retrieval, that is, using text annotation to describe image information, mainly manually labeling images, this type of image retrieval technology is essentially It is a method of text retrieval, and this method also brings some disadvantages: manual labeling is highly subjective, consumes a lot of manpower and material resources, etc.; the other is content-based image retrieval, which uses some content characteristics of images for retrieval , such as the color, texture, layout and other...

AI Technical Summary

Problems solved by technology

[0005] The problem of calculating the similarity of massive images has always been one of the important issues in the field of content-based image retrieval. Even if the locality-sensitive hash algorithm can greatly speed up the retrieval process, when the amount of data increases exponentially, it will still seriously affect the retrieval process. Efficiency, but also requires considerable hardware support

[0009] 3) In particular, when the amount of image data reaches a certain level, the complexity of the image features will greatly affect the retrieval time, and it will also put forward higher requirements for the hardware

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