Halcon實現(xiàn)

思路：

通過中值濾波后，對圖像進(jìn)行動態(tài)閾值提取細(xì)化缺陷部分，結(jié)合開運(yùn)算，閉運(yùn)算提取缺陷。

read_image (Image, 'D:/opencv練習(xí)圖片/復(fù)雜背景提取缺陷.jpg')

dev_set_line_width (3)

threshold (Image, Region, 30, 255)

reduce_domain (Image, Region, ImageReduced)

mean_image (ImageReduced, ImageMean, 150, 150)

dyn_threshold (ImageReduced, ImageMean, SmallRaw, 37, 'dark')

opening_circle (SmallRaw, RegionOpening,4.5)

closing_circle (RegionOpening, RegionClosing, 7)

connection (RegionClosing, ConnectedRegions)

dev_set_color ('red')

dev_display (Image)

dev_set_draw ('margin')

dev_display (ConnectedRegions)

 Opencv實現(xiàn)

 實現(xiàn)方法與思路:

原圖轉(zhuǎn)灰度圖后使用核大小201（奇數(shù)）做中值濾波；

灰度圖與濾波圖像做差,閾值處理

形態(tài)學(xué)進(jìn)一步提取缺陷

輪廓查找，通過面積篩選缺陷，顯示

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int main(int argc, char** argv)

{

    Mat src = imread("D:/opencv練習(xí)圖片/復(fù)雜背景提取缺陷.jpg");

    imshow("輸入圖像", src);

    Mat gray, gray_mean,dst,binary1, binary2, binary;

    cvtColor(src, gray, COLOR_BGR2GRAY);

    medianBlur(gray, gray_mean, 201);

    imshow("中值濾波", gray_mean);

    addWeighted(gray, -1, gray_mean, 1, 0, dst);

    imshow("做差", dst);

    //閾值提取

    threshold(dst, binary1, 10, 255, THRESH_BINARY|THRESH_OTSU);

    imshow("二值化", binary1);

    Mat src_open, src_close;

    //形態(tài)學(xué)

    Mat kernel = getStructuringElement(MORPH_ELLIPSE, Size(7, 7), Point(-1, -1));

    morphologyEx(binary1, src_open, MORPH_OPEN, kernel, Point(-1, -1));

    imshow("開運(yùn)算", src_open);

    morphologyEx(src_open, src_close, MORPH_CLOSE, kernel, Point(-1, -1));

    imshow("閉運(yùn)算", src_close);

    vector<vector<Point>>contours;

    findContours(src_close, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE, Point());

    for (int i = 0; i < contours.size(); i++)

    {

        float area = contourArea(contours[i]);

        cout << area << endl;

        if (area > 1000)

        {

            drawContours(src, contours, i, Scalar(0, 0, 255), 2, 8);

        }

    }

    imshow("結(jié)果", src);

    waitKey(0);

    return 0;

}