【摘要】：隨著信息技術(shù)的發(fā)展，IC(Integrated Circuit)技術(shù)在國防、航天航空、通信等各行各業(yè)及日常生活中得到了廣泛應(yīng)用。機(jī)器視覺技術(shù)作為IC封裝設(shè)備的關(guān)鍵共性技術(shù)，伴隨著IC封裝產(chǎn)業(yè)的發(fā)展而逐漸走向成熟。由于研發(fā)比較早、技術(shù)比較成熟，國外的商用機(jī)器視覺軟件包占據(jù)了絕大部分市場份額，如MIL、HALCON和Congex等。這些視覺軟件包使用方便、性能穩(wěn)定、效率較高，但是費(fèi)用昂貴。因此，研發(fā)擁有自主知識產(chǎn)權(quán)的視覺軟件包具有重大的意義。本文對視覺軟件包中的圖像匹配算法進(jìn)行了研究，分別提出了基于Zernike矩的灰度匹配算法和基于廣義Hough變換的特征匹配算法，以滿足IC封裝設(shè)備中對定位技術(shù)高速度、高精度、適應(yīng)旋轉(zhuǎn)的應(yīng)用要求。 圖像匹配算法可以分為兩個大類，基于灰度的匹配算法和基于特征的匹配算法。基于灰度的匹配方法對噪聲具有較好的魯棒性，與特征匹配相比較，其能夠適用模糊圖像的匹配。基于特征的匹配方法對光照有較強(qiáng)的適應(yīng)性，且能夠?qū)埲�、遮擋等情況進(jìn)行匹配。基于灰度和基于特征的匹配算法各有其優(yōu)缺點(diǎn)，在應(yīng)用中應(yīng)該結(jié)合實(shí)際情況選擇合適的匹配方法。 在基于灰度匹配算法中，提出了基于Zernike矩的快速匹配算法。首先根據(jù)三角函數(shù)的對稱性，僅需要計(jì)算八分之一個圓內(nèi)的Zernike矩基函數(shù)值，快速計(jì)算Zernike矩；然后通過求取圖像多個矩的互相關(guān)性，確定匹配點(diǎn)的像素位置；進(jìn)而通過最小二乘擬合，得到亞像素位置；最后利用Zernike矩的相位信息，估算旋轉(zhuǎn)角度。同時，采用離線階段建立RCS表，保存與快速計(jì)算Zernike矩的相關(guān)信息，在線階段查找RCS表的方法進(jìn)一步加速匹配算法。實(shí)驗(yàn)結(jié)果表明，該算法位置匹配精度可以達(dá)到0.5個像素內(nèi)，角度匹配精度可以達(dá)到0.1°以上，快速算法匹配速度為非快速算法的2~3倍。 在基于特征匹配算法中，提出了適應(yīng)旋轉(zhuǎn)的廣義Hough變換匹配算法。該算法在廣義Hough變換思想的基礎(chǔ)上，利用梯度方向與旋轉(zhuǎn)角度之間的關(guān)系，實(shí)現(xiàn)對存在旋轉(zhuǎn)的圖像進(jìn)行投票匹配。并對投票模型進(jìn)行了分析，提出了高斯投票模型。在理論分析的基礎(chǔ)上，設(shè)計(jì)實(shí)現(xiàn)了該算法。首先在離線階段建立Rtable；然后在在線階段查找Rtable，對匹配位置和匹配角度進(jìn)行投票，得到位置和角度；最后利用最小二乘擬合，得到亞像素位置和角度。通過測試結(jié)果可知，該算法能夠?qū)崿F(xiàn)對旋轉(zhuǎn)圖像進(jìn)行匹配，位置匹配精度可以達(dá)到0.5個像素內(nèi)，角度匹配精度可以達(dá)到0.5°以上，，零角度匹配時間為16ms，全角度匹配時間為70ms。
[Abstract]:With the development of information technology, IC (Integrated Circuit) technology has been widely used in national defense, aerospace, communications and other industries and daily life. Machine vision technology, as the key common technology of IC packaging equipment, has gradually matured with the development of IC packaging industry. Because of the early R & D and mature technology, most of the foreign software packages, such as MIL,HALCON and Congex, occupy most of the market share. These visual software packages are easy to use, stable, efficient, but expensive. Therefore, it is of great significance to develop visual software packages with independent intellectual property rights. In this paper, the image matching algorithm in visual software package is studied, and the gray level matching algorithm based on Zernike moment and the feature matching algorithm based on generalized Hough transform are proposed, respectively, to satisfy the high speed and high precision of positioning technology in IC packaging equipment. Adapt to the application of rotation requirements. Image matching algorithms can be divided into two categories: gray-based matching algorithm and feature-based matching algorithm. The method based on gray level is robust to noise. Compared with feature matching, it can be used to match fuzzy images. The feature-based matching method has strong adaptability to illumination and can match incomplete occlusion and other cases. The matching algorithm based on gray level and feature has its own advantages and disadvantages, so the suitable matching method should be selected according to the actual situation in the application. In the grayscale matching algorithm, a fast matching algorithm based on Zernike moment is proposed. Firstly, according to the symmetry of trigonometric function, the Zernike moment basis function in an eighth circle is only calculated, and the Zernike moment is calculated quickly, then the pixel position of the matching point is determined by calculating the mutual correlation of several moments in the image. Then the sub-pixel position is obtained by least square fitting. Finally, the rotation angle is estimated by using the phase information of Zernike moment. At the same time, the RCS table is set up in the off-line stage to save and quickly calculate the relevant information of the Zernike moment, and the method of searching the RCS table in the online phase further accelerates the matching algorithm. The experimental results show that the accuracy of position matching can reach 0.5 pixels, the precision of angle matching can reach 0.1 擄, and the matching speed of the fast algorithm is 2 times than that of the non-fast algorithm. In the feature matching algorithm, the generalized Hough transform matching algorithm adapted to rotation is proposed. Based on the idea of generalized Hough transform and the relationship between gradient direction and rotation angle, the algorithm realizes the voting matching of images with rotation. The voting model is analyzed and Gao Si voting model is put forward. On the basis of theoretical analysis, the algorithm is designed and implemented. Firstly, the Rtable; is established in the off-line phase, and then the Rtable, is found in the online stage to vote on the matching position and the matching angle. Finally, the location and angle of the sub-pixel are obtained by least square fitting. The test results show that the algorithm can match rotating images, the accuracy of position matching can reach 0.5 pixels, the precision of angle matching can reach 0.5 擄, the time of zero-angle matching is 16ms. The full angle matching time is 70 Ms.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP391.41

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