Method for identifying content of digital video

Abstract

The invention belongs to the technical field of the video processing, and particularly relates to a method for identifying content of a digital video, which mainly comprises a key frame extraction module, a video copy detection module and a video frame content identification module. The video copy detection module adopts a video copy detection method based on local ordering to ensure that a similar frame is rapidly obtained through a given possibility, and to improve the detection performance. The video frame content identification module adopts a pornographic image identification algorithm, the algorithm comprises four weak classifiers (skin area proportion classifier, face quantity classifier, invariant-moment classifier and skin area distribution classifier), the four weak classifiers are integrated to form one strong classifier, the result of the strong classifier is the final detection result, so the mistake recognition rate and nonrecognition rate can be effectively reduced. The method has wide application value for the internet digital video information monitoring.

Description

technical field [0001] The invention belongs to the technical fields of digital video processing, multimedia information management and control, etc., and specifically relates to a method for content recognition of digital video, which can be used in occasions requiring digital video control in various multimedia information management and control. Background technique [0002] With the development of multimedia technology and network communication technology, while digital media brings convenience to people, it also brings some potential risks, such as the proliferation of pornographic and harmful content. How to effectively control these network multimedia information and ensure the security of network content has become one of the main contents of research on bad information retrieval and monitoring. [0003] Most of the existing network filtering systems are based on the filtering of URL addresses. This technology simply blocks the website URLs in the network operator's ...

AI Technical Summary

Problems solved by technology

[0003] Most of the existing network filtering systems are based on URL address filtering. This technology simply blocks the website URLs in the network operator's "blacklist" (has been identified as bad websites by the network operator)

Although the URL-based blocking technology is simple and efficient, it has serious limitations: 1. Network operators cannot update the "blacklist" in real time, and some newly-added bad websites have thus slipped through the net; 2. , Simple URL shielding may cause many normal website contents to be blocked innocently

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