Method and system for correcting brightness of text image

Abstract

The invention discloses a method and system for correcting the brightness of a text image. The method comprises the following steps of: performing gray scale morphological closed operation on an original text image to acquire a background gray scale image of the original text image; performing Gaussian smooth processing, sampling background gray scale data obtained after the Gaussian smooth processing, and performing curved surface fitting to acquire a background gray scale curved surface; and traversing pixel points in the original text image and pixel points of a corrected image, calculating brightness correction coefficients of the pixel points according to a background gray scale fit image and correcting the brightness of the original text image. As the background brightness is estimated by adopting a morphological method and the Gaussian smooth processing is performed so that the curved surface fit can be carried out to acquire a mathematical description for the background brightness; aiming at the brightness correction coefficient corresponding to each pixel point in the image, correction of the text image with the non-uniform background brightness can be finished; therefore, good input data can be supplied to the subsequent image analysis and understanding processes.

Description

Technical field [0001] The invention relates to the field of text image processing. More specifically, the improvement relates to a method and system for correcting the brightness of a text image. Background technique [0002] When using digital cameras and other imaging equipment to shoot objects with uniform brightness, the brightness around the image will gradually decrease, which is the so-called loss of light; any optical lens will more or less cause loss of light, resulting in uneven brightness Phenomenon; in many computer vision applications, this uneven brightness phenomenon will also have a negative impact on subsequent image analysis and understanding; for example, when segmenting text in an image, uneven brightness will cause segmentation The difficulty increases. The method to reduce the effect of loss of light is currently mainly to reduce the aperture during shooting, or to use image processing tools for correction in the later stage. [0003] However, the above two...

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Problems solved by technology

[0003] However, the above two methods have their own disadvantages: if shooting in a dark environment, narrowing the aperture means prolonging the exposure time, and the prolongation of the exposure time requires high stability for handheld shooting. It is very easy to make the image blurry; and using image processing tools to correct the brightness in the later stage is mainly an interactive image correction, and the grasp of the correction scale is relatively subjective, so it is difficult to be more objective in computer vision applications to automate the process

[0004] Therefore, the existing technology still needs to be improved and developed

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