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Method for recognizing compressed-domain sensitive images based on visual attention models

A visual attention model and sensitive image technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problem of lack of feature description operators that accurately describe image sensitive information

Active Publication Date: 2013-02-20
BEIJING UNIV OF TECH
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Problems solved by technology

It provides an important solution to the problem of lack of feature description operators that accurately describe image sensitive information.

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  • Method for recognizing compressed-domain sensitive images based on visual attention models
  • Method for recognizing compressed-domain sensitive images based on visual attention models
  • Method for recognizing compressed-domain sensitive images based on visual attention models

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Embodiment Construction

[0045] According to the above description, the following is a specific implementation process, but the protection scope of this patent is not limited to this implementation process. The following is the specific workflow of the present invention: firstly, starting from the characteristics of sensitive images, a visual attention model is established to detect sensitive areas in the image that meet people's subjective feelings, and then extract the color, texture, brightness and skin color features in the area to construct a visual word library, and finally According to the distribution of these words in the image, the pattern classification method of support vector machine is used to identify and filter sensitive images.

[0046] 1. Construction of visual vocabulary:

[0047] The present invention starts from the characteristics of sensitive images, uses compressed domain image processing technology, and according to the human eye visual attention mechanism, establishes a visua...

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Abstract

The invention discloses a method for recognizing compressed-domain sensitive images based on visual attention models, and belongs to the image recognition field. Prior methods for recognizing sensitive images based on visual words are improved, visual attention models are built according to human visual attention mechanisms, sensitive areas in accordance with human subjective feelings are detected, and relevant characteristics are extracted to generate a visual word bank, accordingly, representation of the visual words is improved effectively, characteristics capable of describing image sensitive information accurately are obtained, and the purpose for improving sensitive image recognition accuracy is achieved. Besides, the invention further provides a compressed-domain sensitive image processing technology, characteristics of joint photographic experts group (JPEG) image compressed data are used, the sensitive areas of images are detected rapidly, and characteristics of the sensitive areas are extracted, so that visual word bank building and image recognition speeds are increased effectively.

Description

technical field [0001] The present invention takes the sensitive images in the JPEG compression format in the network as the research object (the present invention refers to pornographic images in particular), uses compression domain image processing technology, establishes a visual attention model for sensitive images according to the human eye attention visual mechanism, and focuses on analyzing the Sensitive (erotic) areas, extracting color, texture, brightness and skin color features in sensitive areas, constructing a visual word library describing sensitive image content, and then using support vector machine image recognition based on the distribution of these sensitive visual words in the image The method identifies and filters sensitive images, and provides a sensitive image identification and filtering method based on human visual attention for the field of network information supervision. Background technique [0002] With the rapid development of Internet technolo...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/66
Inventor 张菁隋磊卓力李振伟
Owner BEIJING UNIV OF TECH
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