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Image meaning automatic marking method based on marking significance sequence

A technology for automatic image labeling and automatic labeling, which is applied in image data processing, image data processing, special data processing applications, etc., and can solve problems such as obvious negative effects.

Inactive Publication Date: 2007-02-28
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As the amount of data increases, the negative effects of this problem will become more and more obvious

Method used

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  • Image meaning automatic marking method based on marking significance sequence
  • Image meaning automatic marking method based on marking significance sequence
  • Image meaning automatic marking method based on marking significance sequence

Examples

Experimental program
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Embodiment 1

[0085] Given 6,000 images, 5,000 of which already contain annotation information as a training image set for the annotation method, the embodiment performs automatic image annotation on the remaining 1,000 images.

[0086] (1) First classify the training image set with a support vector machine to form a subset of images with consistent content. In this embodiment, 50 image subsets are formed, and each subset has about 100 images, as shown in FIG. 3 , several images classified into the image subset "horse".

[0087] (2) Image segmentation is performed on the images in each image subset to form several image sub-blocks, and the image sub-blocks are clustered. The 20 classes formed after the image subset "horse" is segmented and clustered. Attached Figure 4 and Figure 5 are the image sub-block collection diagrams contained in the two semantic sub-blocks, respectively representing "horse" and "grassland" , which can be represented by the underlying feature cluster centers of the ...

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Abstract

The invention relates to an image mantic automatic mark method based on mark importance sequence, wherein it comprises: (1) classifying the training images, to form a serial of same image groups; (2) building mantic skeleton for each image, to express its image with mantic skeleton, at the same time, calculating the keyword importance sequence of image and the importance sequence of image sub block; (3) using static method to automatic mark the image. The invention considers the importance of sub block of image area and the importance sequence of training text, to support the image search based on mantic, without word frequency distortion distribution.

Description

technical field [0001] The invention relates to the technical field of computer multimedia, in particular to an image semantic automatic labeling method based on the order of labeling importance. Background technique [0002] In the field of multimedia retrieval, the content-based retrieval system pre-obtains the visual perception characteristics of images or videos (such as color histograms, textures, shapes, motion vectors, etc.), and requires users to provide features describing the desired images when querying, and then perform matching . This query method is difficult for ordinary users to understand and is difficult to promote and use. In addition, visual perception features are difficult to reflect the concept expressed by the image, and the query accuracy is not high. People are more inclined to use keywords to query on the semantic level, but there is a "semantic gap" in the image data, which makes the traditional content-based image retrieval technology unable to...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06T1/00
Inventor 庄越挺吴飞鲁伟明吴江琴
Owner ZHEJIANG UNIV
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