Method for searching black and white boundary of image

Abstract

The invention relates to a search method for image black and white boundary. It separates the image to several rows and each row has its own image zone. The grey scale average value would be gained by averaging the grey scale value in the image zone of every row. Then, the grey scale reference value would be gained by averaging the grey scale average value. Setting the grey scale reference value as reference, the grey scale average value is set as the white or black grey scale reference value. The grey scale critical value would be gained by counting white or black grey scale reference value. Then, setting the grey scale critical value as the reference, the white or black grey scale conclusion value would be gained by setting white or black grey scale as reference value. The row that has been defined relative to white or black grey scale conclusion value is white row or black row. And the boundary between white row and black row is defined as image black and white boundary.

Description

technical field [0001] The present invention relates to a search method for the black-and-white boundary of an image, and in particular to a search method for the black-white boundary of an image that is applicable to different test patterns and gets rid of the fetters that a test software can only be applied to one kind of picture. method. Background technique [0002] Please refer to FIG. 1 , which shows a top view of a base of a general scanner. In FIG. 1 , the scanner 100 includes a base 101 , and the base 101 includes an upper cover 102 , a scanning platform 104 and an optical engine 106 . The scanning platform 104 is disposed in the upper cover 102 for placing a test pattern 108 , and the side of the test pattern 108 is aligned with the junction of the upper cover 102 and the scanning platform 104 , that is, the reference line 112 . Wherein, the test pattern 108 has a black and white border 110 for dividing the map 108 into a black area and a white area, and the dist...

AI Technical Summary

Problems solved by technology

[0006] However, these two methods must grasp the type and relative position of the test pattern when writing the test software, that is, the limitation that one test software can only be applied to one kind of pattern

When changing different test patterns, it is necessary to modify the test software, which is quite troublesome

In addition, the problem with the above-mentioned first method lies in the determination of the sampling frequency and the objectivity of the sampling points, and the misjudgment caused by poor system cannot be ruled out.

In addition, the above-mentioned second method is suitable for an ideal state. If the difference between the blackest and the whitest is not large, it is very likely to cause misjudgment.

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