項目中需要用到opencv，先了解後做仿照別人做了兩個 關於java Opencv 答題卡掃描 銀行卡號碼截取 的 小程序。
Opencv的安裝下載，就不多介紹，主要是貼代碼，希望大家能多多指教。
答題卡代碼如下
import org.opencv.core.*;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import java.util.*;
import static org.opencv.core.CvType.CV_8U;
import static org.opencv.imgproc.Imgproc.MORPH_RECT;
/**
* @author lsw
* @email [email protected]
*/
public class OpenCv {
static {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
}
public static void main(String []args) {
String sheet = "D://A4.jpg";
//A4 二值化膨脹後生成的圖片路徑
String results = "E://result.jpg";
String msg = rowsAndCols(sheet, results);
System.out.println(msg);
}
public static void Canny(String oriImg, String dstImg, int threshold) {
//裝載圖片
Mat img = Imgcodecs.imread(oriImg);
Mat srcImage2 = new Mat();
Mat srcImage3 = new Mat();
Mat srcImage4 = new Mat();
Mat srcImage5 = new Mat();
//圖片變成灰度圖片
Imgproc.cvtColor(img, srcImage2, Imgproc.COLOR_RGB2GRAY);
//圖片二值化
Imgproc.adaptiveThreshold(srcImage2, srcImage3, 255, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY_INV, 255, 1);
//確定腐蝕和膨脹核的大小
Mat element = Imgproc.getStructuringElement(MORPH_RECT, new Size(1, 6));
//腐蝕操作
Imgproc.erode(srcImage3, srcImage4, element);
//膨脹操作
Imgproc.dilate(srcImage4, srcImage5, element);
//Imgcodecs.imwrite("E:/picpool/card/enresults.jpg", srcImage4);
//確定每張答題卡的ROI區域
Mat imag_ch1 = srcImage4.submat(new Rect(200, 1065, 1930, 2210));
//識別所有輪廓
Vector<MatOfPoint> chapter1 = new Vector<>();
Imgproc.findContours(imag_ch1, chapter1, new Mat(), 2, 3);
Mat result = new Mat(imag_ch1.size(), CV_8U, new Scalar(255));
Imgproc.drawContours(result, chapter1, -1, new Scalar(0), 2);
Imgcodecs.imwrite("E://result.jpg", result);
//new一個 矩形集合 用來裝 輪廓
List<RectComp> RectCompList = new ArrayList<>();
for (int i = 0; i < chapter1.size(); i++) {
Rect rm = Imgproc.boundingRect(chapter1.get(i));
RectComp ti = new RectComp(rm);
//把輪廓寬度區間在 50 - 80 範圍內的輪廓裝進矩形集合
if (ti.rm.width > 60 && ti.rm.width < 85) {
RectCompList.add(ti);
}
}
//new一個 map 用來存儲答題卡上填的答案 (A\B\C\D)
TreeMap<Integer, String> listenAnswer = new TreeMap<>();
//按 X軸 對listenAnswer進行排序
RectCompList.sort((o1, o2) -> {
if (o1.rm.x > o2.rm.x) {
return 1;
}
if (o1.rm.x == o2.rm.x) {
return 0;
}
if (o1.rm.x < o2.rm.x) {
return -1;
}
return -1;
});
/*
如果精度高，可以通過像素計算
for (RectComp rc : RectCompList) {
int x = RectCompList.get(t).getRm().x - 16;
int y = RectCompList.get(t).getRm().y - 94;
//計算x軸上的分割 如果超過5題，那麼還會有一個大分割
int xSplit = x/85 /5;
//因爲第一題 x=21 計算機中題目從0開始算，現實是從1開始 所以+1
int xTitleNum = x/85 + 1;
//由於精度問題 x軸會慢慢遞減 遞減到上一個答案去 如果不跨過兩個答案以上，都沒問題 如果答題卡x軸40題左右 會出問題
if(x%85>20){
System.out.println("x軸遞減程度" + x%85);
xTitleNum++;
}
xTitleNum = xTitleNum - xSplit;
System.out.println(xTitleNum);
}
*/
//根據 Y軸 確定被選擇答案 (A\B\C\D)
for (RectComp rc : RectCompList) {
for (int h = 0; h < 7; h++) {
if ((rc.rm.contains(new Point(rc.rm.x + 20, 115 + (320 * h))))) {
for (int w = 0; w < 4; w++) {
if (rc.rm.contains(new Point(55 + (500 * w), rc.rm.y))) {
listenAnswer.put(1 + (20 * h) + (5 * w), "A");
} else if (rc.rm.contains(new Point(135 + (500 * w), rc.rm.y))) {
listenAnswer.put(2 + (20 * h) + (5 * w), "A");
} else if (rc.rm.contains(new Point(215 + (500 * w), rc.rm.y))) {
listenAnswer.put(3 + (20 * h) + (5 * w), "A");
} else if (rc.rm.contains(new Point(300 + (500 * w), rc.rm.y))) {
listenAnswer.put(4 + (20 * h) + (5 * w), "A");
} else if (rc.rm.contains(new Point(380 + (500 * w), rc.rm.y))) {
listenAnswer.put(5 + (20 * h) + (5 * w), "A");
}
}
} else if ((rc.rm.contains(new Point(rc.rm.x + 20, 165 + (320 * h))))) {
for (int w = 0; w < 4; w++) {
if (rc.rm.contains(new Point(55 + (500 * w), rc.rm.y))) {
listenAnswer.put(1 + (20 * h) + (5 * w), "B");
} else if (rc.rm.contains(new Point(135 + (500 * w), rc.rm.y))) {
listenAnswer.put(2 + (20 * h) + (5 * w), "B");
} else if (rc.rm.contains(new Point(215 + (500 * w), rc.rm.y))) {
listenAnswer.put(3 + (20 * h) + (5 * w), "B");
} else if (rc.rm.contains(new Point(300 + (500 * w), rc.rm.y))) {
listenAnswer.put(4 + (20 * h) + (5 * w), "B");
} else if (rc.rm.contains(new Point(380 + (500 * w), rc.rm.y))) {
listenAnswer.put(5 + (20 * h) + (5 * w), "B");
}
}
} else if ((rc.rm.contains(new Point(rc.rm.x + 20, 220 + (320 * h))))) {
for (int w = 0; w < 4; w++) {
if (rc.rm.contains(new Point(55 + (500 * w), rc.rm.y))) {
listenAnswer.put(1 + (20 * h) + (5 * w), "C");
} else if (rc.rm.contains(new Point(135 + (500 * w), rc.rm.y))) {
listenAnswer.put(2 + (20 * h) + (5 * w), "C");
} else if (rc.rm.contains(new Point(215 + (500 * w), rc.rm.y))) {
listenAnswer.put(3 + (20 * h) + (5 * w), "C");
} else if (rc.rm.contains(new Point(300 + (500 * w), rc.rm.y))) {
listenAnswer.put(4 + (20 * h) + (5 * w), "C");
} else if (rc.rm.contains(new Point(380 + (500 * w), rc.rm.y))) {
listenAnswer.put(5 + (20 * h) + (5 * w), "C");
}
}
} else if ((rc.rm.contains(new Point(rc.rm.x + 20, 275 + (320 * h))))) {
for (int w = 0; w < 4; w++) {
if (rc.rm.contains(new Point(55 + (500 * w), rc.rm.y))) {
listenAnswer.put(1 + (20 * h) + (5 * w), "D");
} else if (rc.rm.contains(new Point(135 + (500 * w), rc.rm.y))) {
listenAnswer.put(2 + (20 * h) + (5 * w), "D");
} else if (rc.rm.contains(new Point(215 + (500 * w), rc.rm.y))) {
listenAnswer.put(3 + (20 * h) + (5 * w), "D");
} else if (rc.rm.contains(new Point(300 + (500 * w), rc.rm.y))) {
listenAnswer.put(4 + (20 * h) + (5 * w), "D");
} else if (rc.rm.contains(new Point(380 + (500 * w), rc.rm.y))) {
listenAnswer.put(5 + (20 * h) + (5 * w), "D");
}
}
}
}
}
Iterator iter = listenAnswer.entrySet().iterator();
while (iter.hasNext()) {
Map.Entry entry = (Map.Entry) iter.next();
Object key = entry.getKey();
Object val = entry.getValue();
System.out.println("第" + key + "題,分數:" + val);
}
}
public static String rowsAndCols(String oriImg, String dstImg) {
String msg = "";
Canny(oriImg, dstImg, 50);
Mat mat = Imgcodecs.imread(dstImg);
msg += "\n行數:" + mat.rows();
msg += "\n列數:" + mat.cols();
msg += "\nheight:" + mat.height();
msg += "\nwidth:" + mat.width();
msg += "\nelemSide:" + mat.elemSize();
//CvType contourSeq = null;
return msg;
}
}
核心代碼如上圖： 還有另外一個類，也很簡單 我就不貼出來了，大家可以去我的github上面找得到 通過核心代碼就能理解出大概的思路。
github地址 : https://github.com/shiwenlin/opencv
銀行卡也很簡單最後是也在github上 項目中截取到銀行卡的圖片，我們也可以用別的插件轉成數字，