BGA（Ball Grid Array）是一種被廣泛使用在IC封裝的技術。對於各種電子產品，如晶片組、CPU、Flash、部份通訊用IC等，其功能與型號是透過雷射刻印其封裝表面所形成印字符號來辨別。因此，為了使其刻印位置達到精確的校準，封裝IC表面的中心位置與方向角需要透過影像檢測系統來量測。

　　本論文提出一次像素BGA晶片校準方法。本方法首先在檢測的區域內利用區域投影法辨識物體的輪廓，藉此定義影像感興趣的區域，並利用DOB來找物體的邊緣點。此外，對於物體邊緣有裂痕或破裂的像素則利用邊緣追隨法過濾掉。接下來利用ZOM (Zernike Orthogonal Moment; 澤尼克正交矩)修正所得的邊緣點，使邊緣點達到次像素精確度。最後，經由最小平方差直線匹配的迴歸演算以及幾何運算，得到校準中心位置與偏向角。

　　本論文針對所提出的方法，利用人工合成影像評估其在高斯雜訊干擾下的穩定性與精確度。實驗結果顯示，在沒有雜訊的干擾下，中心定位誤差維持正負0.1像素，而偏向角誤差維持正負0.01度；在不同程度高斯雜訊的干擾下，誤差標準差全部都小於1.6 %。執行效能方面，在一台備有Pentium 4 3.0GHz處理器的電腦上，完成單次運算程序需要時間約109毫秒，平均檢測範圍為360×300像素。

　BGA (Ball Grid Array), a technology of packaging, is widely used in the integrated circuits. The model name and function of each IC chip through laser marking are to be identified by recognizing the etched mark on package surface. For instance, chip group, CPU, Flash, some communication IC etc. In order to achieve accurate alignment for the location of the etched mark, the central position and orientation angle of an IC package are examined through the image inspection system.

　　This thesis proposed a subpixel alignment method for BGA images. In the method, firstly, region projection is applied to recognize the contour of the object within the inspected area and delimit the regions of interest. Then the edge elements of the object can be found by using DOB (Difference of Boxes). Moreover, the edge elements resulting from cracks or flaws on object’s boundaries are filtered out by edge following method. Next, the edge elements are modified by ZOM (Zernike Orthogonal Moment) to achieve subpixel accuracy. Finally, the central position and orientation angle are obtained by the LSE line fitting algorithm followed by geometric computation.

　　Our proposed method is evaluated in terms of the stability and accuracy under noise degradation for synthetic images. The experimental results show that the error of the central position and the orientation is within ±0.1 pixel and within ±0.01 degree respectively without noise; the error standard deviation of the central position and the orientation are all less than 1.6% under various levels of Gaussian noise corruption. On running performance, it takes approximate 109 ms to complete the entire process for an inspected area of 360×300 pixels while running on a PC equipped with a processor of Pentium 4 3.0GHz.

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