微型精密零件图像测量清晰度算法的选择与综合评价算法

随着仪器、设备的日益小型化，微型精密零件应用日益广泛。由于常规测量手段的局限性，光学影像测量方法在微型精密零件测量中成为国内外竞相发展的技术。然而在图像采集过程中对图像清晰度的评价算法虽种类较多但各算法之间缺乏统一。本论文基于微型精密零件的成像测量方法，使用前人制作的图像测量仪，使用远心成像测量系统在不同工作距离处进行图像采集，然后使用相关算法进行清晰度评价，最后对所得数据进行主成分分析和因子分析，从8种图像清晰度评价算法计算出适用于课题使用的评价算法，并建立了综合清晰度评价模型。本文的数据处理模式能够对算法进行选择并解决不同算法间的协调问题。而且本文提出的数据挖掘算法能针对同一要求的不同评价值进行选择及综合，同时能大幅减少后续运算量。

The selection and overall algorithm of definition algorithm in image measuring apparatus for micro parts

Miniature parts are applied more broadly as instruments and equipments are getting more miniature. Imaging measuring methods used in miniature parts have become an important technology which is developing competitively at home and abroad. The methods are able to solve the limitation of routine measurements. This paper is based on image measuring methods and the image measuring apparatus for micro parts. There are many algorithms which are employed to appraise definition nowadays; however, different algorithms may get different results in different measuring systems and there is not a well-rounded algorithm to tell user how to make choice. So it is not easy to select a certain algorithm according to the characteristic of the appointed apparatus. The aim of his paper is to present an algorithm to deal with the selection of definition and the process in this paper shows typical ways of orientation for Telecentric systems. The procession of the experiment can be mainly divided into three parts. Firstly, the Telecentric image measuring system is used to grab image at different working distances; and the distance between the camera and the benchmark is recorded by a laser interferometer with double frequency. Secondly, the correlative algorithms including Brenner function, Tenengrad function, Gradient square function and the four modifier formula, entropy function are employed to appraise definition in this paper. Finally, the principal component analysis and the factor analysis are employed to analyze the data so as to work out the algorithm which is suitable for the apparatus from the above 8 algorithms and to work out the overall merit algorithm for definition. As a result, the suitable definition algorithm is worked out to be Tenengrad function and the overall merit algorithm for definition is presented. The synthesis evaluating model of definition has also been built in this paper. The data mining algorithm submitted in this paper is able to make choice in different evaluations when aiming at the exclusive requirement and to decrease the amount of the operands which will be used in next programs. The innovation of this paper is that it presents a whole new algorithm to deal with the selection of definition algorithm and a whole new algorithm to overall merit the definition algorithms. The experiment shows that the image grabbing system which using Telecentric systems would capture the most clear picture form series of pictures by using the algorithms.