Image conversion method

Abstract

The invention belongs to the technical field of image conversion and compression, and discloses an image conversion method. The image conversion method comprises the following steps: 101: analyzing an original color image to obtain the color information of all information contents in the image; 102: carrying out weighted processing on the color information, and converting the weighted color image into a grayscale image; 103: analyzing the grayscale image to obtain the resolution of the grayscale image, obtaining an adaptive local range under the resolution, and determining the size of an area impact factor; and 104: traversing the whole image according to the size of the area impact factor, and converting the image into a black-and-white image through an adaptive image binaryzation method with a limited range. By use of the method, the image is clearer after being converted, and is easy in optical recognition.

Description

technical field [0001] The invention belongs to the technical field of image conversion and compression, and in particular relates to an image conversion method. Background technique [0002] With the advancement of enterprise informatization, enterprises now have more and more paper documents and image materials that need to be collected into information systems. During the acquisition process, the text and data of the image need to be optically recognized to the system. At the same time, due to limitations in storage space, transmission speed, etc., the resolution and image bit depth of the image are limited before archiving and saving the image. Usually, the image file conversion method used for image acquisition and optical recognition can be realized. [0003] In the existing image acquisition process, the usual image processing method is to first convert the color image into a grayscale image through RGB conversion coefficients, and then binarize the image through thr...

AI Technical Summary

Problems solved by technology

[0004] 1) When converting a color image to a grayscale image in a unified way, sometimes the contrast is not obvious or the text is too light;

[0005] 2) Converting a grayscale image to a black and white image through a threshold value will result in image distortion with obvious layering;

[0006] 3) Convert grayscale images to black and white images by thresholding. When processing images with background, such as images with background color or scanned shadow images, the recognition rate of blurred characters will be reduced;

[0007] 4) When the image is binarized by self-adaptation, when processing images such as barcodes, sometimes the barcodes will be blurred and the recognition rate will be reduced;

[0008] 5) When binarizing the image through self-adaptation, when dealing with a larger block of background color, the background will be lost

Images