Flat-field correction method, flat-field correction device, image verification method and image verification device

Abstract

The embodiment of the invention provides a flat-field correction method, a flat-field correction device, an image verification method and an image verification device. According to the flat-field correction method, a dark-field image is obtained by adjustment of the exposure time and a gained camera; the incorrect operation due to artificial lens covering is avoided; therefore, the quality of thedark-field image is improved; simultaneously, the operation quantity is reduced through a manner of obtaining the dark-field image by adjusting camera parameters; and thus, the acquisition efficiencyof the dark-field image is effectively increased. By means of the flat-field correction method, average filtering of gray values of various pixel points in an alternate bright-field image is carried out; a high-frequency component is removed by filtration; therefore, quality damage of the alternate bright-field image due to the special situations of fine grains on a white reference, uneven texture, dust on a glass sheet and the like can be reduced; and thus, the quality of the bright-field image is effectively improved. According to the embodiment of the invention, the flat-field correction precision is improved by improving the quality of the dark-field image and the bright-field image; simultaneously, the condition that the dark-field image is obtained by artificial operation is avoided;and the acquisition efficiency of the dark-field image is obtained.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of image processing, and more specifically, to a flat-field correction method and device, and an image verification method and device. Background technique [0002] When the camera is used to image the target object, the gray value of all pixels in the image is theoretically the same. However, the value of each pixel in the actual image often has a large difference. The reasons for this difference mainly include the following: (1) The illumination of the target object is not uniform; (2) The responsivity of the center of the camera lens is inconsistent with the response of the edge of the camera lens; (3) Each pixel in the imaging component of the camera The point response is inconsistent, that is, the ability of each pixel to convert light into charge is different; (4) Fixed Pattern Noise (PFN) of the camera. [0003] Flat-field correction is a correction method used to eliminate the ...

AI Technical Summary

Problems solved by technology

Not only is the efficiency low, but it is also very prone to misoperation due to improper manual coordination, which reduces the quality of dark field images

Bright field images need a white reference object when shooting. In actual shooting, the quality of bright field images may be damaged due to fine particles, uneven texture, dust, etc. on the white reference object.

The reduction of dark field image quality and bright field image quality will reduce the accuracy of flat field correction, which will affect the correction of the gray value of each pixel in the image and affect the shooting quality of the camera.

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