Method for screening useful images from retrieved images

An image-in-image technology, applied in the field of information retrieval, can solve problems such as inability to correlate, affecting sorting accuracy, etc.

Inactive Publication Date: 2014-05-07
XIDIAN UNIV
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Problems solved by technology

[0007] The purpose of the present invention is to propose a method for screening useful images from retrieved images to solve the problem that noise samples affect the sorting accuracy in the existing sorting process, and the problem tha

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  • Method for screening useful images from retrieved images
  • Method for screening useful images from retrieved images

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[0043] Reference figure 1 , The implementation steps of the present invention are as follows:

[0044] 1. Generate a visual semantic dictionary based on the probability distribution of the word frequency feature BOW of visual bag of words and the probability distribution of semantic attributes.

[0045] Step 1: Extract 8192-dimensional visual bag-of-words word frequency features from the initial search result images in the database.

[0046] Step 2: Through offline training and learning, for 2659 basic semantic attributes, train 2659 semantic attribute classifiers. When doing image search, use these 2659 classifiers for each image to make predictions, and each image corresponds to The predicted score vector obtained from the 2659-dimensional feature is used as the attribute feature of the image, and each dimension corresponds to a specific semantic attribute.

[0047] Step 3: Use the mapping function sigmoid to map the semantic attribute features of the training image to the range of...

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Abstract

The invention discloses a method for screening useful images from retrieved images, and is mainly used for solving the problem of low accuracy rate of the current image retrieving sequencing results. The method comprises the following main realization steps that (1) database image visual word bag characteristics and semantic attribute characteristics are extracted; (2) mapping dictionaries of the visual word bag characteristics and the semantic attribute characteristics are trained and learned in an off-line way; (3) the retrieval is carried out according to images to be searched given by users to obtain initial image sequencing lists; (4) the visual word semantic importance is analyzed according to the images to be searched given by the users; (5) the visual word context importance is analyzed according to the images to be searched given by the users; (6) by combining the visual word semantics and the context importance, the relevance score of images to be sequenced is calculated again, and the re-sequencing on initial results is completed, so the users can screen out useful relevant images. The method provided by the invention has the advantages that the final image retrieving accuracy rate can be obviously improved, and the method can be used for image retrieving.

Description

technical field [0001] The invention belongs to the technical field of information retrieval, and specifically relates to a method for screening useful images from retrieved images, which can be used to improve the accuracy of image retrieval results on the Internet. Background technique [0002] With the rapid development of Internet technology, Flicker, Renren, Facebook, Sina Weibo and other social media based on the web2.0 environment are increasingly emerging, which makes it possible to share massive multimedia data such as images and videos. Nowadays, there are a large number of images and videos uploaded on the Internet all the time. At the same time, people are becoming more and more accustomed to searching and querying various information such as images and texts on the Internet. In this context, how to achieve efficient image search that meets the user's search intention becomes very important. Under the current Internet background, commercial search engines such ...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/5838
Inventor 邓成王东旭杨延华王嘉龙李洁高新波
Owner XIDIAN UNIV
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