HSV, SURF and LBP feature combination-based sensitive image identification method

A technology of sensitive images and recognition methods, applied in the field of sensitive image recognition, can solve the problems of low accuracy and slow processing speed of sensitive image recognition methods, and achieve the effects of fast processing speed, high accuracy and good fault tolerance.

Pending Publication Date: 2018-06-08
天津市国瑞数码安全系统股份有限公司
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Problems solved by technology

[0007] The invention provides a sensitive image recognition method based on the combination of HSV, SURF and LBP features, which can effectively solve the problem of slow processing...

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  • HSV, SURF and LBP feature combination-based sensitive image identification method
  • HSV, SURF and LBP feature combination-based sensitive image identification method
  • HSV, SURF and LBP feature combination-based sensitive image identification method

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Embodiment Construction

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0042] Such as figure 1 As shown, the sensitive image recognition method based on the combination of HSV, SURF and LBP features provided by the present invention comprises the following steps:

[0043] Step 1: If figure 2As shown, the skin area of ​​the sensitive RGB image and the normal RGB image are obtained.

[0044] 1.1 Read in 320*280 sensitive RGB images and normal RGB images, use Haar-like features to detect the face areas in sensitive ...

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Abstract

The invention provides an HSV, SURF and LBP feature combination-based sensitive image identification method. The method comprises the steps of obtaining skin regions of a sensitive RGB image and a normal RGB image; obtaining SURF visual vocabulary expressions of the sensitive RGB image and the normal RGB image by using an SURF algorithm; obtaining LBP visual vocabulary expressions of the sensitiveRGB image and the normal RGB image by using an LBP algorithm; obtaining HSV color features of the sensitive RGB image and the normal RGB image by using an HSV color model; by using the SURF visual vocabulary expressions, the LBF visual vocabulary expressions and the HSV color features as input parameters, training a BP neural network; and outputting a to-be-detected image identification result. The HSV, SURF and LBP feature combination method is adopted for performing sensitive image detection, and has the characteristics of high processing speed and high accuracy.

Description

technical field [0001] The invention belongs to the technical field of sensitive image recognition, and in particular relates to a sensitive image recognition method based on the combination of HSV, SURF and LBP features. Background technique [0002] With the rapid development of Internet technology in recent years, online forums and portals have also grown rapidly, covering almost all aspects of life, so the dissemination of Internet picture information is becoming more and more extensive and easy, and the dissemination of harmful images is harmful to young people. negatively affect their physical and mental health and social climate. Due to the large number of people posting and posting pictures in the forum, it will obviously consume a lot of time and energy for forum administrators to review all forum pictures in turn. Therefore, an effective sensitive image recognition method based on machine learning and machine vision will reduce the workload of forum administrators....

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62G06K9/00
CPCG06V40/161G06V40/168G06V40/172G06V10/50G06V10/56G06F18/23213
Inventor 李新夏光升孙涛郝振江李小标柴军民
Owner 天津市国瑞数码安全系统股份有限公司
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