Character detection method and device

Abstract

The invention discloses a character detection method and a device. The character detection method comprises steps of receiving image to be detected, generating a character area probability graph of the whole text of the image to be detected which is generated by a semantic prediction model, wherein the character area probability graph uses different the pixel value area to distinguish the Chinese character area of the image to be detected and the non-Chinese character area of the image to be detected and performing segmentation operation on the probability graph of the Chinese character area in order to determine the Chinese character area. The Character detection method disclosed by the invention can detect the characters of various languages, directions, colors, fonts and sizes while effectively inhibiting the interference of the complex background. Besides, the Chinese character detection method and the device have characteristics of strong robustness and effectively resisting the interferences of the image noise, image fuzziness, the complex image background and the non-uniform light irradiation.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a character detection method and device. Background technique [0002] With the widespread popularity of smart phones and the rapid development of the mobile Internet, acquiring, retrieving and sharing information through the cameras of mobile terminals such as mobile phones has gradually become a way of life. Camera-based applications put more emphasis on the understanding of the shooting scene. Usually, in a scene where text and other objects coexist, users tend to pay more attention to the text information in the scene first, so correctly identifying the text in the image will have a deeper understanding of the user's shooting intention. This involves text detection techniques to identify text areas in captured images. [0003] As an important basic technology, text detection has great application value and broad application prospects, especially text detection in natural sce...

AI Technical Summary

Problems solved by technology

[0004] However, most of the images to be detected contain complex backgrounds, and their quality may be affected by factors such as noise, blur, and non-uniform lighting; in addition, texts are diverse, for example, texts in natural scene images may have different colors , size, font, orientation, etc.

These factors will bring great difficulties and challenges to text detection.

Based on the above reasons, the existing text detection methods are prone to false alarms, that is, the non-text components in the background are mistakenly identified as text

In addition, the existing text detection methods also have shortcomings in terms of adaptability. For example, most methods can only detect horizontal text, but cannot do anything for tilted or rotated text.

For another example, some methods can only be applied to Chinese detection, and cannot be directly extended to texts of different languages ​​(such as English, Russian, Korean, etc.)

Moreover, when there is serious noise, blur or non-uniform illumination in the image, the existing text detection methods often produce errors.

In short, the existing text detection methods and systems have shortcomings in terms of accuracy and scope of application.

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