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, and more specifically, the improvement relates to a method and system for correcting brightness of text images. Background technique [0002] When using an imaging device such as a digital camera to shoot an object with uniform brightness, the brightness around the image will gradually decrease, which is the so-called loss of light; any optical lens will cause loss of light more or less, resulting in uneven brightness phenomenon; in many computer vision applications, this phenomenon of uneven brightness will also have a negative impact on subsequent image analysis and understanding; for example, when segmenting text in an image, uneven brightness will lead to segmentation increased difficulty. The methods to reduce the effect of light loss mainly include reducing the aperture when shooting, or using image processing tools to correct in the later stage. [0003] However, the above two method...

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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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