直接上代碼，代碼每一步都是解釋與插圖，一步步實作，如果不清楚opencv的環境如何搭建，可上網查或者參見我的前幾篇部落格，不多說了， java代碼如下：
package com.zmx.opencvtest;
import org.opencv.core.*;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
/**
* Created by zhangwenchao on 2017/9/27.
*/
public class FirstOpenCVTest {
static {
//注意程式運作的時候需要在VM option添加該行 指明opencv的dll檔案所在路徑
//-Djava.library.path=$PROJECT_DIR$\opencv\x64
System.loadLibrary(Core.NATIVE_LIBRARY_NAME); //載入opencv all庫
}
public static void main(String[] args) throws InterruptedException {
/**
* 1. 讀取原始圖像轉換為OpenCV的Mat資料格式
*/
Mat srcMat = Imgcodecs.imread("E:/srcImage.jpg"); //原始圖像
/**
* 2. 強原始圖像轉化為灰階圖像
*/
Mat grayMat = new Mat(); //灰階圖像
Imgproc.cvtColor(srcMat, grayMat, Imgproc.COLOR_RGB2GRAY);
BufferedImage grayImage = toBufferedImage(grayMat);
saveJpgImage(grayImage,"E:/grayImage.jpg");
System.out.println("儲存灰階圖像！");
/**
* 3、對灰階圖像進行二值化處理
*/
Mat binaryMat = new Mat(grayMat.height(),grayMat.width(),CvType.CV_8UC1);
Imgproc.threshold(grayMat, binaryMat, 20, 255, Imgproc.THRESH_BINARY);
BufferedImage binaryImage = toBufferedImage(binaryMat);
saveJpgImage(binaryImage,"E:/binaryImage.jpg");
System.out.println("儲存二值化圖像！");
/**
* 4、圖像腐蝕---腐蝕後變得更加寬,粗.便于識别--使用3*3的圖檔去腐蝕
*/
Mat destMat = new Mat(); //腐蝕後的圖像
Mat element = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(3, 3));
Imgproc.erode(binaryMat,destMat,element);
BufferedImage destImage = toBufferedImage(destMat);
saveJpgImage(destImage,"E:/destImage.jpg");
System.out.println("儲存腐蝕化後圖像！");
/**
* 5 圖檔切割
*/
//擷取截圖的範圍--從第一行開始周遊,統計每一行的像素點值符合門檻值的個數,再根據個數判斷該點是否為邊界
//判斷該行的黑色像素點是否大于一定值（此處為150）,大于則留下,找到上邊界,下邊界後立即停止
int a =0, b=0, state = 0;
for (int y = 0; y < destMat.height(); y++)//行
{
int count = 0;
for (int x = 0; x < destMat.width(); x++) //列
{
//得到該行像素點的值
byte[] data = new byte[1];
destMat.get(y, x, data);
if (data[0] == 0)
count = count + 1;
}
if (state == 0)//還未到有效行
{
if (count >= 150)//找到了有效行
{//有效行允許十個像素點的噪聲
a = y;
state = 1;
}
}
else if (state == 1)
{
if (count <= 150)//找到了有效行
{//有效行允許十個像素點的噪聲
b = y;
state = 2;
}
}
}
System.out.println("過濾下界"+Integer.toString(a));
System.out.println("過濾上界"+Integer.toString(b));
//參數,坐标X,坐标Y,截圖寬度,截圖長度
Rect rect = new Rect(0,a,destMat.width(),b - a);
Mat resMat = new Mat(destMat,rect);
BufferedImage resImage = toBufferedImage(resMat);
saveJpgImage(resImage,"E:/resImage.jpg");
System.out.println("儲存切割後圖像！");
/**
* 識别-
*/
/* try {
Process pro = Runtime.getRuntime().exec(new String[]{"D:/Program Files (x86)/Tesseract-OCR/tesseract.exe", "E:/resImage.jpg","E:/result"});
pro.waitFor();
} catch (IOException e) {
e.printStackTrace();
}*/
try {
String result = TesseractOCRUtil.recognizeText(new File("E:/resImage.jpg"));
System.out.println(result);
} catch (Exception e) {
e.printStackTrace();
}
}
/**
* 将Mat圖像格式轉化為 BufferedImage
* @param matrix mat資料圖像
* @return BufferedImage
*/
private static BufferedImage toBufferedImage(Mat matrix) {
int type = BufferedImage.TYPE_BYTE_GRAY;
if (matrix.channels() > 1) {
type = BufferedImage.TYPE_3BYTE_BGR;
}
int bufferSize = matrix.channels() * matrix.cols() * matrix.rows();
byte[] buffer = new byte[bufferSize];
matrix.get(0, 0, buffer); // 擷取所有的像素點
BufferedImage image = new BufferedImage(matrix.cols(), matrix.rows(), type);
final byte[] targetPixels = ((DataBufferByte)image.getRaster().getDataBuffer()).getData();
System.arraycopy(buffer, 0, targetPixels, 0, buffer.length);
return image;
}
/**
* 将BufferedImage記憶體圖像儲存為圖像檔案
* @param image BufferedImage
* @param filePath 檔案名
*/
private static void saveJpgImage(BufferedImage image, String filePath) {
try {
ImageIO.write(image, "jpg", new File(filePath));
} catch (Exception e) {
throw new RuntimeException(e);
}
}
}
對于圖檔識别，我單獨寫了一個工具類，本文也有引用，java代碼如下：
package com.zmx.opencvtest;
/**
* Created by zhangwenchao on 2017/9/28.
*/
import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.List;
public class TesseractOCRUtil{
private static final String LANG_OPTION = "-l";
private static final String EOL = System.getProperty("line.separator");
/**
* @param imageFile
* 傳入的圖像檔案
* @return 識别後的字元串
*/
public static String recognizeText(File imageFile) throws Exception {
/**
* 設定輸出檔案的儲存的檔案目錄
*/
File outputFile = new File(imageFile.getParentFile(), "output");
StringBuffer strB = new StringBuffer();
Process pro = Runtime.getRuntime().exec(
new String[]{
"D:/Program Files (x86)/Tesseract-OCR/tesseract.exe",
imageFile.getPath(),
outputFile.getPath()}
);
int w = pro.waitFor();
if (w == 0) // 0代表正常退出
{
BufferedReader in = new BufferedReader(new InputStreamReader(
new FileInputStream(outputFile.getAbsolutePath() + ".txt"),
"UTF-8"));
String str;
while ((str = in.readLine()) != null)
{
strB.append(str).append(EOL);
}
in.close();
} else
{
String msg;
switch (w)
{
case 1:
msg = "Errors accessing files. There may be spaces in your image's filename.";
break;
case 29:
msg = "Cannot recognize the image or its selected region.";
break;
case 31:
msg = "Unsupported image format.";
break;
default:
msg = "Errors occurred.";
}
throw new RuntimeException(msg);
}
new File(outputFile.getAbsolutePath() + ".txt").delete();
return strB.toString().replaceAll("\\s*", "");
}
public static void main(String[] args) {
try {
String result = recognizeText(new File("E:/resImage.jpg"));
System.out.println(result);
} catch (Exception e) {
e.printStackTrace();
}
}
}
運作結果如下：
1、原始圖像（網上不知哪位仁兄的銀行卡）：
2、儲存灰階圖像！
3、儲存二值化圖像！
4、儲存腐蝕化後圖像！
5、擷取的截取圖像的上下邊界
過濾上界386
過濾下界447
6、儲存切割後圖像！
7、識别的卡号：
6228482298797273578
搞了一天的時間，總算大功告成，效果還不錯！