Processing method for measuring sub-pixel rim of digital picture

Abstract

The invention discloses a digital image measurement sub-pixel edge processing method which carries out a bulk processing on the image edge by adopting a gradient model, takes a gradient mean as the threshold of the binaryzation control, realizes a search of binaryzation images in the biggest connected region on the basis of a flood filling principle and searches consecutive points of which a segment of gradient values exceeds the gradient threshold at all location points in four direction; the direction which has the smallest number of consecutive points is the direction of normal; a gradient peak value along the direction of normal is calculated on base of a spline interpolation subdivision algorithm; edge points contained on a fitting curve is marked from the collected target rough edges; after multiple rounds of iterative computations, if all points on the collected target rough edges are marked, the precise sub-pixel edge computation is finished. The processing method of the invention bases on traditional gradient edge extraction, flood filling algorithm and spline interpolation subdivision algorithm; the processing course is realized through a crude image processing and a refined image processing; the target edge is searched on purpose; the computational efficiency is high and the algorithm course takes the requirement of the noise suppression into consideration and increases the immunity of the algorithm.

Description

technical field [0001] The invention relates to an image measurement processing method, in particular to a digital image measurement sub-pixel edge processing method. Background technique [0002] With the current development of digital information technology, digital image processing technology is becoming more and more important, and has been widely used in many production and living scenes. At present, digital image measurement technology also occupies a very important position in the field of photoelectric detection. One of its most important contents is to realize the precise positioning of the edge of the image target. This is especially important in digital image measurement applications. It can be said that accurate and fast extraction of image edges in digital image measurement applications is the basis and key to extract image-related information. [0003] Current digital images are all two-dimensional plane images. According to the different CCD photosensitive c...

AI Technical Summary

Problems solved by technology

[0019] 1. Because the binarization result is affected by the eigenvalue control threshold, the image processing result is too artificially affected, the algorithm is not universal for images in different applications, and it is not conducive to the realization of automatic computer programs;

[0020] 2. There are many kinds of noise in the processing image. Although the traditional algorithm hopes to achieve the purpose of noise suppression by changing the correlation operator or the auxiliary filtering algorithm, it has little effect on different image applications, which is not conducive to real-time image processing;

[0021] 3. The edge positioning of the target image is not accurate, and the processing result is too rough, which is difficult to meet the application requirements of precise image measurement. At the same time, there are great limitations in many applications requiring precise image processing.

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