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优化算法

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devA
yuxue 5 years ago
parent afb9562ffa
commit bbaaf25fdb
1 changed files with 52 additions and 155 deletions
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205
src/main/java/com/yuxue/util/ImageUtil.java
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@ -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);
// 去除小连通区域
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, false, tempPath);
Mat d = clearHole(c, 3, 8, false, tempPath);
if (debug) {
Imgcodecs.imwrite(tempPath + (debugMap.get("morphology") + 100) + "_morphology0.jpg", dst);
Imgcodecs.imwrite(tempPath + (debugMap.get("morphology") + 100) + "_morphology0.jpg", d);
}
// 去除小连通区域
Mat a = clearSmallConnArea(dst, 3, 8, debug, tempPath);
Mat b = clearSmallConnArea(a, 8, 3, debug, tempPath);
// 去除孔洞
Mat c = clearHole(b, 3, 8, debug, tempPath);
Mat d = clearHole(c, 3, 8, debug, tempPath);
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<Integer> 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<Point2d> neihbor = new Vector<Point2d>();// 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<Point2d> GrowBuffer = new Vector<Point2d>(); // 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++) {
@ -814,8 +715,4 @@ public class ImageUtil {
}

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