Image sorting method based on local colors and distribution characteristics of characteristic points

Abstract

The invention discloses an image sorting method based on local colors and distribution characteristics of characteristic points, which mainly solves the problem of the poor effectiveness of image characteristic description and the ambiguity in image understanding in the prior art. The method comprises the following steps of: firstly, performing scale normalization and rotation normalization on the image, and detecting characteristic points; then, dividing the normalized image into a series of fan-shaped sub-regions with unequal acreage according to the distribution of the characteristic points, and extracting the local colors and the space distribution characteristics of the characteristic points in each sub-region, generating a characteristic vector, measuring the similarity and orderingthe sub-regions; taking the image as a multi-instance package to obtaining characteristics of a target image through a multi-instance learning method; and finally, recalculating the similarity, and outputting the sorting result. The method not only improves the effectiveness of the image characteristic description, but also reduces the ambiguity in the process of sorting out the images, so that the method can sort out internet images more accurately, and can be used for searching image information in the internet.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image sorting method, which can be used for searching image information in the Internet. Background technique [0002] The rapid development of computer technology and Internet technology makes it easy for people to share resources. Multimedia information represented by digital images and audio / videos is widely disseminated on the Internet. How to quickly and efficiently detect users from massive image databases? The desired image is a challenging problem. Content-based image sorting is a research hotspot in the field of multimedia in recent years by extracting features from images and performing similarity measurement with images in the image library to sort out images. The traditional method uses the global feature of the image to sort out, but due to the large amount of calculation of the global feature, and many times the user is only interested in a certain obje...

AI Technical Summary

Problems solved by technology

There are two problems in the image sorting method based on feature points: (1) The extracted image features mainly reflect the local characteristics of feature points, and less consider the spatial distribution structure of feature points, so the effectiveness of image feature description is not enough ; (2) Due to the difference between the underlying visual features of the image and the rich semantic features of the user, the results of image sorting are ambiguous

Both of these affect the accuracy of image picking

Images