Method for facula center positioning of CCD image measurement system

Abstract

The invention provides a method for facula center positioning of a CCD image measurement system. According to the method, a facula image generated by a CCD sensor is simulated by means of software, denoising is carried out on a laser facula generated by simulation by means of median filtering, binarization is then carried out on the denoised image, edge extraction is carried out on the image treated with binarization by means of the Gauss-Laplace operator, then primary positioning is carried out by means of the gray level gravity method, and finally accurate positioning is carried out on the primarily positioned image by means of the Gaussian curvefitting algorithm. According to the method, due to the introduction of the image pre-processing step, noise in the image can be effectively filtered, and interference resistance is improved; due to the fact that only useful data points in the image are calculated and analyzed, the calculated amount is small, and then realization of the software is easy and resources of the system are saved greatly.

Description

technical field [0001] The invention relates to a method for measuring and positioning, in particular to a method for measuring and positioning the center of a light spot. Background technique [0002] Patent CNIO1465002 (disclosure date: June 24, 2009) discloses a sub-pixel edge location method for elliptical objects. The method is mainly divided into three steps. The first step is image denoising and Sobel operator edge detection 1. Extracting the edge points of the ellipse object; the second step is to use the edge points to obtain the geometric parameters of the ellipse object; the third step is to locate the sub-pixel edge. [0003] Precise positioning of the center of the laser spot projected on the CCD during image measurement is an important prerequisite for ensuring measurement accuracy. With the improvement of measurement accuracy requirements, pixel-level accuracy can no longer meet the requirements of actual measurement, and higher accuracy is required The extra...

AI Technical Summary

Problems solved by technology

[0004] For the precise positioning of laser spots, the most commonly used center positioning sub-pixel algorithms include gray-scale center of gravity method, interpolation method, correlation method, and moment method. The algorithm is simple and has high positioning accuracy, which can reach 0.2 to 0.5 pixels. The method can only process images with a moderate target area, and is greatly disturbed by noise. When the signal-to-noise ratio of the image is small, its positioning error will become very large

At the same time, the Gaussian curve fitting method is also a mathematical method used more in image processing, but its positioning accuracy is related to the specific distribution of the image. In actual processing, it is often necessary to analyze each image in detail, and the language description is complex and requires consumes a lot of program running time

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