PCB印刷缺陷檢測（自定義結構元素）

摘要

本篇來用OpenCV實現Halcon中一個簡單的PCB印刷缺陷檢測實例。 Halcon中對應的例子為pcb_inspection.hdev。並自定義一個正八邊形結構元素進行開運算，閉運算，然后做差將缺陷標記顯示。

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原圖如下：

Halcon代碼比較簡單，這里也貼出來，短短13行：

read_image (Image, 'pcb')
dev_close_window ()
get_image_size (Image, Width, Height)
dev_open_window (0, 0, Width, Height, 'black', WindowHandle)
dev_display (Image)
* detect defects ...
gray_opening_shape (Image, ImageOpening, 7, 7, 'octagon')
gray_closing_shape (Image, ImageClosing, 7, 7, 'octagon')
dyn_threshold (ImageOpening, ImageClosing, RegionDynThresh, 75, 'not_equal')
dev_display (Image)
dev_set_color ('red')
dev_set_draw ('margin')
dev_display (RegionDynThresh)

opencv實現：

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 （一）自定義正八邊形結構元素

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    Mat gray,src_open,src_close,dst;
    Mat src = imread("D:/opencv練習圖片/pcb缺陷檢測.png");
    imshow("原圖", src);
    cvtColor(src, gray, COLOR_RGB2GRAY);
    Mat kernel = Mat::ones(Size(7, 7), CV_8UC1);
    kernel.at<uchar>(0, 0) = 0;
    kernel.at<uchar>(0, 1) = 0;
    kernel.at<uchar>(0, 5) = 0;
    kernel.at<uchar>(0, 6) = 0;
    kernel.at<uchar>(1, 0) = 0;
    kernel.at<uchar>(1, 6) = 0;
    kernel.at<uchar>(5, 0) = 0;
    kernel.at<uchar>(5, 6) = 0;
    kernel.at<uchar>(6, 0) = 0;
    kernel.at<uchar>(6, 1) = 0;
    kernel.at<uchar>(6, 5) = 0;
    kernel.at<uchar>(6, 6) = 0;
    cout << kernel << endl;

 這里對矩陣的分別賦值，其實有一個填充函數fillPloy（）（只需輸入頂點坐標即可）

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 （二）對圖像開運算，閉運算，做差

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    morphologyEx(gray, src_open, MORPH_OPEN, kernel);
    imshow("開運算", src_open);
    morphologyEx(gray, src_close, MORPH_CLOSE, kernel);
    imshow("閉運算", src_close);
    absdiff(src_open, src_close, dst);
    imshow("做差", dst);

 開運算：                                                                                                                                   

 閉運算：

 

 二者做差：

 可以看到，白色的點就是缺陷的位置。

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 （三）二值化，尋找輪廓，顯示

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    threshold(dst, dst, 80, 255, THRESH_BINARY);
    vector<vector<Point>>contours;
    findContours(dst, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE, Point());
    drawContours(src, contours, -1, Scalar(0, 0, 255), 2, 8);
    imshow("顯示缺陷", src);

 

 參考於：OpenCV與AI深度學習