diff --git a/src/main/java/com/yuxue/util/ImageUtil.java b/src/main/java/com/yuxue/util/ImageUtil.java index b0d6da42..00c2259e 100644 --- a/src/main/java/com/yuxue/util/ImageUtil.java +++ b/src/main/java/com/yuxue/util/ImageUtil.java @@ -11,6 +11,8 @@ import org.opencv.core.CvType; import org.opencv.core.Mat; import org.opencv.core.MatOfPoint; import org.opencv.core.MatOfPoint2f; +import org.opencv.core.Point; +import org.opencv.core.Rect; import org.opencv.core.RotatedRect; import org.opencv.core.Scalar; import org.opencv.core.Size; @@ -20,21 +22,6 @@ import org.opencv.ml.ANN_MLP; import org.opencv.ml.SVM; import com.google.common.collect.Lists; -/* -import org.bytedeco.javacpp.BytePointer; -import org.bytedeco.javacpp.opencv_core; -import org.bytedeco.javacpp.Core.Mat; -import org.bytedeco.javacpp.Core.MatVector; -import org.bytedeco.javacpp.Core.Point2d; -import org.bytedeco.javacpp.Core.Point2f; -import org.bytedeco.javacpp.Core.RotatedRect; -import org.bytedeco.javacpp.Core.Scalar; -import org.bytedeco.javacpp.Core.Size; -import org.bytedeco.javacpp.opencv_ml.ANN_MLP; -import org.bytedeco.javacpp.opencv_ml.SVM; -import org.bytedeco.javacpp.opencv_imgcodecs; -import org.bytedeco.javacpp.opencv_imgproc; -*/ import com.google.common.collect.Maps; @@ -281,16 +268,16 @@ public class ImageUtil { Size size = new Size(DEFAULT_MORPH_SIZE_WIDTH, DEFAULT_MORPH_SIZE_HEIGHT); Mat element = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, size); Imgproc.morphologyEx(inMat, dst, Imgproc.MORPH_CLOSE, element); - - if (debug) { - Imgcodecs.imwrite(tempPath + (debugMap.get("morphology") + 100) + "_morphology0.jpg", dst); - } // 去除小连通区域 - Mat a = clearSmallConnArea(dst, 3, 8, debug, tempPath); - Mat b = clearSmallConnArea(a, 8, 3, debug, tempPath); + Mat a = clearSmallConnArea(dst, 3, 8, false, tempPath); + Mat b = clearSmallConnArea(a, 8, 3, false, tempPath); // 去除孔洞 - Mat c = clearHole(b, 3, 8, debug, tempPath); - Mat d = clearHole(c, 3, 8, debug, tempPath); + Mat c = clearHole(b, 3, 8, false, tempPath); + Mat d = clearHole(c, 3, 8, false, tempPath); + + if (debug) { + Imgcodecs.imwrite(tempPath + (debugMap.get("morphology") + 100) + "_morphology0.jpg", d); + } return d; } @@ -477,8 +464,8 @@ public class ImageUtil { for (int i = 0; i < nRows; ++i) { for (int j = 0; j < nCols; j += 3) { int H = (int)inMat.get(i, j)[0]; - int S = (int)inMat.get(i, j)[1]; - int V = (int)inMat.get(i, j)[2]; + // int S = (int)inMat.get(i, j)[1]; + // int V = (int)inMat.get(i, j)[2]; if(map.containsKey(H)) { int count = map.get(H); map.put(H, count+1); @@ -487,7 +474,7 @@ public class ImageUtil { } } } - Set set = map.keySet(); + Set set = map.keySet(); Object[] arr = set.toArray(); Arrays.sort(arr); for (Object key : arr) { @@ -504,12 +491,12 @@ public class ImageUtil { * @param inMat * @return */ - /*public static RotatedRect maxAreaRect(Mat threshold, Point2f point2f) { + public static Rect maxAreaRect(Mat threshold, Point point) { int edge[] = new int[4]; - edge[0] = (int) point2f.x() + 1;//top - edge[1] = (int) point2f.x() + 1;//right - edge[2] = (int) point2f.y() - 1;//bottom - edge[3] = (int) point2f.x() - 1;//left + edge[0] = (int) point.x + 1;//top + edge[1] = (int) point.y + 1;//right + edge[2] = (int) point.y - 1;//bottom + edge[3] = (int) point.x - 1;//left boolean[] expand = { true, true, true, true};//扩展标记位 int n = 0; @@ -518,14 +505,10 @@ public class ImageUtil { expand[edgeID] = expandEdge(threshold, edge, edgeID); n++; } - //[3] - //qDebug() << edge[0] << edge[1] << edge[2] << edge[3]; - Point tl = Point(edge[3], edge[0]); - Point br = Point(edge[1], edge[2]); + Point tl = new Point(edge[3], edge[0]); + Point br = new Point(edge[1], edge[2]); return new Rect(tl, br); - - return null; - }*/ + } /** @@ -540,7 +523,7 @@ public class ImageUtil { int nr = img.rows(); switch (edgeID) { - /*case 0: + case 0: if (edge[0] > nr) { return false; } @@ -556,7 +539,7 @@ public class ImageUtil { return false; } for (int i = edge[2]; i <= edge[0]; ++i) { - if (img.ptr(i, edge[1]).getInt() == 255) + if (img.get(i, edge[1])[0] == 255) return false; } edge[1]++; @@ -566,7 +549,7 @@ public class ImageUtil { return false; } for (int i = edge[3]; i <= edge[1]; ++i) { - if (img.ptr(edge[2], i).getInt() == 255) + if (img.get(edge[2], i)[0] == 255) return false; } edge[2]--; @@ -576,123 +559,20 @@ public class ImageUtil { return false; } for (int i = edge[2]; i <= edge[0]; ++i) { - if (img.ptr(i, edge[3]).getInt() == 255) + if (img.get(i, edge[3])[0] == 255) return false; } edge[3]--; - return true;*/ + return true; default: return false; } } - - /** - * 对于二值图，0代表黑色，255代表白色。 - * 去除小连通区域与孔洞，小连通区域用8邻域，孔洞用4邻域 - * removeSmallRegion(dst, erzhi,100, 1, 1); - * removeSmallRegion(erzhi, erzhi,100, 0, 0); - * https://blog.csdn.net/dajiyi1998/article/details/60601410# - * @param Src 二值图 - * @param Dst 返回值 - * @param AreaLimit 100 - * @param checkMode 0代表去除黑区域，1代表去除白区域 - * @param mode 0代表4邻域，1代表8邻域; - */ - public static void removeSmallRegion(Mat Src, Mat Dst, int AreaLimit, int checkMode, int mode, Boolean debug, String tempPath) { - // 新建一幅标签图像初始化为0像素点，为了记录每个像素点检验状态的标签，0代表未检查，1代表正在检查,2代表检查不合格（需要反转颜色），3代表检查合格或不需检查 - // 初始化的图像全部为0，未检查; 全黑图像 - Mat PointLabel = new Mat(Src.size(), CvType.CV_8UC1); - // Imgcodecs.imwrite(tempPath + "99_remove.jpg", PointLabel); - - /*if (checkMode == 1) {// 去除小连通区域的白色点 - for (int i = 0; i < Src.rows(); i++) { - for (int j = 0; j < Src.cols(); j++) { - if (Src.ptr(i, j).getInt() < 10) { - PointLabel.ptr(i, j).putInt(3); // 将背景黑色点标记为合格，像素为3 - } - } - } - } else {// 去除孔洞，黑色点像素 - for (int i = 0; i < Src.rows(); i++) { - for (int j = 0; j < Src.cols(); j++) { - if (Src.ptr(i, j).getInt() > 10) { - PointLabel.ptr(i, j).putInt(3);// 如果原图是白色区域，标记为合格，像素为3 - } - } - } - } - - Vector neihbor = new Vector();// 将邻域压进容器 - neihbor.add(new Point2d(-1, 0)); - neihbor.add(new Point2d(1, 0)); - neihbor.add(new Point2d(0, -1)); - neihbor.add(new Point2d(0, 1)); - if (mode == 1) { // 8邻域 - neihbor.add(new Point2d(-1, -1)); - neihbor.add(new Point2d(-1, 1)); - neihbor.add(new Point2d(1, -1)); - neihbor.add(new Point2d(1, 1)); - } - - int neihborCount = 4 + 4 * mode; - int CurrX = 0, CurrY = 0; - // 开始检测 - for (int i = 0; i < Src.rows(); i++) { - for (int j = 0; j < Src.cols(); j++) { - if (PointLabel.ptr(i, j).getInt() == 0) {// 标签图像像素点为0，表示还未检查的不合格点 - - Vector GrowBuffer = new Vector(); // 记录检查像素点的个数 - GrowBuffer.add(new Point2d(j, i)); - PointLabel.ptr(i, j).putInt(1);// 标记为正在检查 - int CheckResult = 0; - - for (int z = 0; z < GrowBuffer.size(); z++) { - for (int q = 0; q < neihborCount; q++) { - CurrX = (int) (GrowBuffer.get(z).x() + neihbor.get(q).x()); - CurrY = (int) (GrowBuffer.get(z).y() + neihbor.get(q).y()); - - if (CurrX >= 0 && CurrX < Src.cols() && CurrY >= 0 && CurrY < Src.rows()) { // 防止越界 - if (PointLabel.ptr(CurrY, CurrX).getInt() == 0) { - GrowBuffer.add(new Point2d(CurrX, CurrY)); // 邻域点加入buffer - PointLabel.ptr(CurrY, CurrX).putInt(1); // 更新邻域点的检查标签，避免重复检查 - } - } - } - } - - if (GrowBuffer.size() > AreaLimit) { // 判断结果（是否超出限定的大小），1为未超出，2为超出 - CheckResult = 2; - } else { - CheckResult = 1; - } - for (int z = 0; z < GrowBuffer.size(); z++) { - CurrX = (int) GrowBuffer.get(z).x(); - CurrY = (int) GrowBuffer.get(z).y(); - PointLabel.ptr(CurrY, CurrX).putInt(CheckResult);// 标记不合格的像素点，像素值为2 - } - } - } - } - - // 开始反转面积过小的区域 - checkMode = 255 * (1 - checkMode); - for (int i = 0; i < Src.rows(); ++i) { - for (int j = 0; j < Src.cols(); ++j) { - if (PointLabel.ptr(i, j).getInt() == 2) { - Dst.ptr(i, j).putInt(checkMode); - } else if (PointLabel.ptr(i, j).getInt() == 3) { - Dst.ptr(i, j).put(Src.ptr(i, j)); - } - } - }*/ - } - - /** * 清除二值图像的黑洞 * 按矩形清理 - * @param inMat 二值图像 + * @param inMat 二值图像 0代表黑色，255代表白色 * @param rowLimit 像素值 * @param colsLimit 像素值 * @param debug @@ -718,10 +598,23 @@ public class ImageUtil { int y1 = j - colsLimit < 0 ? 0 : j - colsLimit ; int y2 = j + colsLimit >= inMat.cols() ? inMat.cols()-1 : j + colsLimit ; + int count = 0; + if(inMat.get(x1, y1)[0] > 10) {// 左上角 + count++; + } + if(inMat.get(x1, y2)[0] > 10) { // 左下角 + count++; + } + if(inMat.get(x2, y1)[0] > 10) { // 右上角 + count++; + } + if(inMat.get(x2, y2)[0] > 10) { // 右下角 + count++; + } // 根据中心点+limit，定位四个角生成一个矩形， // 将四个角都是白色的矩形，内部的黑点标记为 要被替换的对象 - if(inMat.get(x1, y1)[0] > 10 && inMat.get(x1, y2)[0] > 10 && inMat.get(x2, y1)[0] > 10 && inMat.get(x2, y2)[0] > 10 ) { + if(count >=4 ) { for (int n = x1; n < x2; n++) { for (int m = y1; m < y2; m++) { if (inMat.get(n, m)[0] < 10 && label.get(n, m)[0] == uncheck) { @@ -748,7 +641,15 @@ public class ImageUtil { return dst; } - + /** + * 清除二值图像的细小连接 + * @param inMat + * @param rowLimit + * @param colsLimit + * @param debug + * @param tempPath + * @return + */ public static Mat clearSmallConnArea(Mat inMat, int rowLimit, int colsLimit, Boolean debug, String tempPath) { int uncheck = 0, black = 1, white = 2; @@ -783,8 +684,8 @@ public class ImageUtil { count++; } - // 根据中心点+limit，定位四个角生成一个矩形， - // 将四个角都是白色的矩形，内部的黑点标记为 要被替换的对象 + // 根据 中心点+limit，定位四个角生成一个矩形， + // 将四个角都是黑色的矩形，内部的白点标记为 要被替换的对象 if(count >= 4) { for (int n = x1; n < x2; n++) { for (int m = y1; m < y2; m++) { @@ -811,10 +712,6 @@ public class ImageUtil { return dst; } - - - -