Test paper image correction method and related device

Abstract

The invention discloses a test paper image correction method. The method comprises the steps of obtaining test paper image data; performing identifier detection on the test paper image data to obtainan identifier; and correcting the test paper image data according to the identifier to obtain corrected test paper image data. According to the test paper image data correction method and device, identifier detection is carried out on the obtained test paper image data to obtain the identifier, and the test paper image data is further corrected according to the obtained identifier instead of overall detection on the test paper image data, so that the image detection area is reduced, and the test paper image data correction efficiency is improved. The invention also discloses a test paper imagecorrection system, a test paper image correction device and a computer readable storage medium, which have the above beneficial effects.

Description

technical field [0001] The present application relates to the technical field of image processing, and in particular to a test paper image correction method, a test paper image correction system, a test paper image correction device, and a computer-readable storage medium. Background technique [0002] With the continuous development of information technology, automated operations can be used to replace repetitive and complex actions, while improving operational efficiency and reducing the waste of personnel costs in repeated operations. Especially in the process of modifying a large number of test papers, due to the characteristics of the test papers, automatic operation can be used to effectively improve the efficiency of modifying the test papers. In the process of automatic marking, scanning equipment or digital cameras are usually used to obtain digital images of test papers. [0003] However, when using a scanning device or a digital camera to obtain digital images of...

AI Technical Summary

Problems solved by technology

[0004] However, the traditional Hough transform algorithm for detecting straight lines is slow, and will detect a large number of noise line segments, which reduces the accuracy of image correction, while the texture correction method has a very large amount of calculation, which affects the operating efficiency of the entire system and reduces the cost of the test paper image correction process. efficiency, and the accuracy of image correction cannot be guaranteed

Images