Java使用OpenCV和Tesseract-OCR实现银行卡图片处理与卡号识别

╰+哭是因爲堅強的太久メ 2022-06-08 14:48 762阅读 0赞

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）：

![Center][]

2、保存灰度图像！

![Center 1][]

3、保存二值化图像！

![Center 2][]

4、保存腐蚀化后图像！

![Center 3][]

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！

![Center 4][]  
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！

[Center]: /images/20220608/bdc301ccbf7a4249aee8d57d7bb9d940.png
[Center 1]: /images/20220608/77260a971e584ad3be31fec5a902a468.png
[Center 2]: /images/20220608/8719388dc5e546b494ecf4cf8886dba4.png
[Center 3]: /images/20220608/51cfcf7ffeb8471987afaf49c680da53.png
[Center 4]: /images/20220608/c550a2db63cd4af4a311c2d52771d939.png