Training optimization pornographic picture or video detection method based on convolutional neural network

Abstract

The invention relates to a training optimization pornographic picture or video detection method based on a convolutional neural network. A final detection model is obtained through circuit training, classification detection accuracy can be improved to a largest extent, and deficiencies that a perfect complexion model and high detection accuracy are difficult to establish due to ambient light diversity and race diversity and the detection accuracy is always low due to external factors, such as human body gesture diversity, sheltering and the like can be overcome. When the method disclosed by the invention is used for picture data or video data to detect pictures or a video image sequence, only a classification result shows that the pictures or video image sequence is pornographic, a picture set or videos are defined as pornographic data, and a deficiency that a universal rule is difficult to establish for different pornographic videos is overcome.

Description

technical field [0001] The present invention relates to a pornographic image detection method, more specifically, relates to a training optimized pornographic image or video detection method based on a convolutional neural network. Background technique [0002] With the widespread use of the Internet, users will also encounter bad information while obtaining a large amount of useful information, especially pornographic images and pornographic videos. Existing pornographic image or pornographic video detection methods mainly use skin color for identification, but in practical applications, existing detection methods have the following factors that limit the detection accuracy: [0003] 1) The diversity of ambient light and the diversity of races make it difficult to establish a perfect skin color model and the accuracy of detection; [0004] 2) External factors such as diversity of human body poses and occlusion make the detection accuracy not high; [0005] 3) It is diffic...

AI Technical Summary

Problems solved by technology

Existing pornographic image or pornographic video detection methods mainly use skin color for identification, but in practical applications, existing detection methods have the following factors that limit the detection accuracy:

[0003] 1) The diversity of ambient light and the diversity of races make it difficult to establish a perfect skin color model and the accuracy of detection;

[0004] 2) External factors such as diversity of human body poses and occlusion make the detection accuracy not high;

[0005] 3) It is difficult to establish more general rules for different pornographic videos

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