Detection method and detection system for video image text

Abstract

The invention discloses a detection method and a detection system for video image text and relates to the technical field of image text detection. The method comprises the following steps of coarse positioning of video image text areas and verification of video image text areas. The specific steps are as follows: (A) coarse positioning of video image text area: the gaussian pyramid multi-scale image of a video image is calculated, the image text area is segmented by threshold segmentation, text areas are combined by the inflation and corrosion technology in mathematical morphology, and candidate text areas are analyzed and positioned by connected domain analysis, text line segmentation and elimination rules; and (B) verification of video image text areas: an adaboost classifier is trained by adopting harr characteristics, and the adaboost classifier is utilized to detect whether text exists in the candidate text areas and the candidate text areas the text of which is not detected are eliminated. The method and the system can improve the accuracy and the recall ratio of video image text detection.

Description

technical field [0001] The invention relates to the technical field of image text detection, in particular to a video image text detection method and system. Background technique [0002] With the development of digital network, there are more and more digital images and videos. Text in pictures or videos can provide direct high-level semantic information. Therefore, the development of video image text detection technology is helpful to understand and manage video images. For example, the detection and analysis of text content in pictures helps to provide effective features for filtering and monitoring of bad content pictures. The title in news video usually indicates the time, place and person of the news, which provides support for the analysis and retrieval of news content. , the score of the game, and the player's number play an important role in automatic video content analysis and wonderful sports moment detection. In natural scenes, image and text also contain import...

AI Technical Summary

Problems solved by technology

When the background is complex, this kind of method often cannot get better classification results by directly using texture features.

[0007] Due to the different sizes of text in video images, different lengths of video text lines, various font colors, and low contrast between text and images, traditional methods have defects such as low accuracy and recall of text detection.

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