Method for calculating and regulating picture and word separation efficacy of image

Abstract

The invention relates to a method for calculating and adjusting the image-text separation effect of an image. The method for calculating image-text separation efficiency includes a step of generating a standard block attribute file, and a step of comparing an image-text separation result with the standard block attribute file to display an image-text separation efficiency data table. In the method for adjusting the image-text separation effect of an image of the present invention, it includes a step of comparing an image-text separation result with the standard block attribute file to generate the image-text separation effect data table, and according to the image-text separation effect data Table is the step of judging whether to use another image-text separation algorithm or parameter value to perform another image-text separation operation.

Description

technical field [0001] The invention relates to a method for calculating the photocopying efficiency applied to a multi-functional business machine and adjusting the image-text separation effect of an image, in particular to a method capable of displaying a specific accuracy rate of image-text separation. Background technique [0002] In the photocopying function of a multifunctional business machine, the original is generally scanned by the scanning module of the multifunctional business machine and the pixel data of the original is stored in the buffer, and then these pixel data are taken out from the buffer for further processing. A series of image processing procedures. These image processing procedures are carried out by some image processing modules, these modules include, for example, color gamut conversion (color space conversion, CSC) module, color picture text separation (color photo / text separation, color PTS) module, color background shifting A color background ...

AI Technical Summary

Problems solved by technology

The number of blocks that need to be checked for each image is very large and the size of the blocks usually divided is very small, so using manual recognition is not only time-consuming, but also causes fatigue to the human eye

In addition, since there is no set of objective measurement tools, multiple judges often produce different judgment results, but it is impossible to clearly determine whose judgment result is correct, and it is also impossible to provide a unified judgment standard for Multiple developers have common rules to follow

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