直接上代码，代码每一步都是解释与插图，一步步实现，如果不清楚opencv的环境如何搭建，可上网查或者参见我的前几篇博客，不多说了， java代码如下：
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 {
//注意程序运行的时候需要在VM option添加该行 指明opencv的dll文件所在路径
//-Djava.library.path=$PROJECT_DIR$\opencv\x64
System.loadLibrary(Core.NATIVE_LIBRARY_NAME); //载入opencv all库
}
public static void main(String[] args) throws InterruptedException {
/**
* 1. 读取原始图像转换为OpenCV的Mat数据格式
*/
Mat srcMat = Imgcodecs.imread("E:/srcImage.jpg"); //原始图像
/**
* 2. 强原始图像转化为灰度图像
*/
Mat grayMat = new Mat(); //灰度图像
Imgproc.cvtColor(srcMat, grayMat, Imgproc.COLOR_RGB2GRAY);
BufferedImage grayImage = toBufferedImage(grayMat);
saveJpgImage(grayImage,"E:/grayImage.jpg");
System.out.println("保存灰度图像！");
/**
* 3、对灰度图像进行二值化处理
*/
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("保存二值化图像！");
/**
* 4、图像腐蚀---腐蚀后变得更加宽,粗.便于识别--使用3*3的图片去腐蚀
*/
Mat destMat = new Mat(); //腐蚀后的图像
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("保存腐蚀化后图像！");
/**
* 5 图片切割
*/
//获取截图的范围--从第一行开始遍历,统计每一行的像素点值符合阈值的个数,再根据个数判断该点是否为边界
//判断该行的黑色像素点是否大于一定值（此处为150）,大于则留下,找到上边界,下边界后立即停止
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
{
//得到该行像素点的值
byte[] data = new byte[1];
destMat.get(y, x, data);
if (data[0] == 0)
count = count + 1;
}
if (state == 0)//还未到有效行
{
if (count >= 150)//找到了有效行
{//有效行允许十个像素点的噪声
a = y;
state = 1;
}
}
else if (state == 1)
{
if (count <= 150)//找到了有效行
{//有效行允许十个像素点的噪声
b = y;
state = 2;
}
}
}
System.out.println("过滤下界"+Integer.toString(a));
System.out.println("过滤上界"+Integer.toString(b));
//参数,坐标X,坐标Y,截图宽度,截图长度
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("保存切割后图像！");
/**
* 识别-
*/
/* 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图像格式转化为 BufferedImage
* @param matrix mat数据图像
* @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); // 获取所有的像素点
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内存图像保存为图像文件
* @param image BufferedImage
* @param filePath 文件名
*/
private static void saveJpgImage(BufferedImage image, String filePath) {
try {
ImageIO.write(image, "jpg", new File(filePath));
} catch (Exception e) {
throw new RuntimeException(e);
}
}
}
对于图片识别，我单独写了一个工具类，本文也有引用，java代码如下：
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
* 传入的图像文件
* @return 识别后的字符串
*/
public static String recognizeText(File imageFile) throws Exception {
/**
* 设置输出文件的保存的文件目录
*/
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();
}
}
}
运行结果如下：
1、原始图像（网上不知哪位仁兄的银行卡）：
2、保存灰度图像！
3、保存二值化图像！
4、保存腐蚀化后图像！
5、获取的截取图像的上下边界
过滤上界386
过滤下界447
6、保存切割后图像！
7、识别的卡号：
6228482298797273578
搞了一天的时间，总算大功告成，效果还不错！