import com.sun.org.apache.xml.internal.security.exceptions.Base64DecodingException;
import com.sun.org.apache.xml.internal.security.utils.Base64;
import com.sun.xml.internal.messaging.saaj.util.ByteInputStream;
import org.apache.http.HttpStatus;
import org.apache.http.StatusLine;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClientBuilder;
import javax.imageio.ImageIO;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.net.URL;
import java.util.*;
import java.util.List;
public class OCRUtil {
private static Map<BufferedImage, String> trainMap = null;
private static int index = 0;
//private static final String dirPath = "D:\Proli\pic\One\";
private static final String dirPath = "";
private static boolean isBlack(int colorInt) {
Color color = new Color(colorInt);
return color.getRed() + color.getGreen() + color.getBlue() <= 100;
}
/**
* 获得二值化图像
* 最大类间方差法
*
* @param gray
* @param width
* @param height
* @return
*/
private static int getOstu(int[][] gray, int width, int height) {
int grayLevel = 256;
int[] pixelNum = new int[grayLevel];
//计算所有色阶的直方图
for (int x = 0; x < width; x++) {
for (int y = 0; y < height; y++) {
int color = gray[x][y];
pixelNum[color]++;
}
}
double sum = 0;
int total = 0;
for (int i = 0; i < grayLevel; i++) {
sum += i * pixelNum[i]; //x*f(x)质量矩，也就是每个灰度的值乘以其点数（归一化后为概率），sum为其总和
total += pixelNum[i]; //n为图象总的点数，归一化后就是累积概率
}
double sumB = 0;//前景色质量矩总和
int threshold = 0;
double wF = 0;//前景色权重
double wB = 0;//背景色权重
double maxFreq = -1.0;//最大类间方差
for (int i = 0; i < grayLevel; i++) {
wB += pixelNum[i]; //wB为在当前阈值背景图象的点数
if (wB == 0) { //没有分出前景后景
continue;
}
wF = total - wB; //wB为在当前阈值前景图象的点数
if (wF == 0) {//全是前景图像，则可以直接break
break;
}
sumB += (double) (i * pixelNum[i]);
double meanB = sumB / wB;
double meanF = (sum - sumB) / wF;
//freq为类间方差
double freq = (double) (wF) * (double) (wB) * (meanB - meanF) * (meanB - meanF);
if (freq > maxFreq) {
maxFreq = freq;
threshold = i;
}
}
return threshold;
}
/**
* 图片预处理 灰度化、二值化、去噪
* @param img
* @return
* @throws Exception
*/
private static BufferedImage removeBackgroud(BufferedImage img) throws Exception {
int width = img.getWidth();
int height = img.getHeight();
double Wr = 0.299;
double Wg = 0.587;
double Wb = 0.114;
int[][] gray = new int[width][height];
//灰度化
for (int x = 0; x < width; x++) {
for (int y = 0; y < height; y++) {
Color color = new Color(img.getRGB(x, y));
int rgb = (int) ((color.getRed() * Wr + color.getGreen() * Wg + color.getBlue() * Wb) / 3);
gray[x][y] = rgb;
}
}
int ostu = getOstu(gray, width, height);
for (int x = 0; x < width; ++x) {
for (int y = 0; y < height; ++y) {
if (gray[x][y] > ostu) {
img.setRGB(x, y, Color.white.getRGB());
} else {
img.setRGB(x, y, Color.black.getRGB());
}
}
}
//去噪
for (int x = 0; x < width; ++x) {
for (int y = 0; y < height; ++y) {
if (isBlack(img.getRGB(x, y))) {
if (isAlone(img, x, y,width,height)) {
img.setRGB(x, y, Color.WHITE.getRGB());
}
}
}
}
return img;
}
/**
* 是否单个噪点 目前判断当前像素点的上下左右4个点是否有黑点，可判断8个方位点
* @param img
* @param x
* @param y
* @param width
* @param height
* @return
*/
private static boolean isAlone(BufferedImage img, int x, int y,int width,int height) {
if (x == 0 || width - x < 3 || y == 0 || height - y < 3) {
return true;
}
try {
int a1 = img.getRGB(x - 1, y + 1);
int a2 = img.getRGB(x - 1, y);
int a3 = img.getRGB(x - 1, y - 1);
int a4 = img.getRGB(x, y + 1);
int a5 = img.getRGB(x, y - 1);
int a6 = img.getRGB(x + 1, y + 1);
int a7 = img.getRGB(x + 1, y);
int a8 = img.getRGB(x + 1, y - 1);
ArrayList<Boolean> booleans = new ArrayList<Boolean>();
booleans.add(isBlack(a1));
booleans.add(isBlack(a2));
booleans.add(isBlack(a3));
booleans.add(isBlack(a4));
booleans.add(isBlack(a5));
booleans.add(isBlack(a6));
booleans.add(isBlack(a7));
booleans.add(isBlack(a8));
long count = booleans.stream().filter((a) -> a).count();
if (count <= 1) {
return true;
}
} catch (Exception e) {
return false;
}
return false;
}
/**
* 移除空白像素
* @param img
* @return
* @throws Exception
*/
private static BufferedImage removeBlank(BufferedImage img) throws Exception {
int width = img.getWidth();
int height = img.getHeight();
int start = 0;
int end = 0;
Label1:
for (int y = 0; y < height; ++y) {
for (int x = 0; x < width; ++x) {
if (isBlack(img.getRGB(x, y))) {
start = y;
break Label1;
}
}
}
Label2:
for (int y = height - 1; y >= 0; --y) {
for (int x = 0; x < width; ++x) {
if (isBlack(img.getRGB(x, y))) {
end = y;
break Label2;
}
}
}
return img.getSubimage(0, start, width, end - start + 1);
}
/**
* 分割图片
* @param img
* @return
* @throws Exception
*/
private static List<BufferedImage> splitImage(BufferedImage img) throws Exception {
List<BufferedImage> subImgs = new ArrayList<>();
int width = img.getWidth();
int height = img.getHeight();
List<Integer> weightlist = new ArrayList<>();
for (int x = 0; x < width; ++x) {
int count = 0;
for (int y = 0; y < height; ++y) {
if (isBlack(img.getRGB(x, y))) {
count++;
}
}
weightlist.add(count);
}
for (int i = 0; i < weightlist.size(); i++) {
int length = 0;
while (i < weightlist.size() && weightlist.get(i) > 0) {
i++;
length++;
}
if (length > 2) {
subImgs.add(removeBlank(img.getSubimage(i - length, 0, length, height)));
}
}
return subImgs;
}
/**
* 加载训练图片
* @return
* @throws Exception
*/
private static Map<BufferedImage, String> loadTrainData() throws Exception {
if (trainMap == null) {
Map<BufferedImage, String> map = new HashMap<>();
File dir = new File(dirPath + "train");
File[] files = dir.listFiles();
for (File file : files) {
map.put(ImageIO.read(file), file.getName().charAt(0) + "");
}
trainMap = map;
}
return trainMap;
}
/**
* 匹配单个图片信息
* @param img
* @param map
* @return
*/
private static String getSingleCharOcr(BufferedImage img,
Map<BufferedImage, String> map) {
String result = "#";
int width = img.getWidth();
int height = img.getHeight();
int min = width * height;
for (BufferedImage bi : map.keySet()) {
int count = 0;
if (Math.abs(bi.getWidth() - width) > 2)
continue;
int widthmin = width < bi.getWidth() ? width : bi.getWidth();
int heightmin = height < bi.getHeight() ? height : bi.getHeight();
Label1:
for (int x = 0; x < widthmin; ++x) {
for (int y = 0; y < heightmin; ++y) {
if (isBlack(img.getRGB(x, y)) != isBlack(bi.getRGB(x, y))) {
count++;
if (count >= min) {
break Label1;
}
}
}
}
if (count < min) {
min = count;
result = map.get(bi);
}
if(count == 0 && min == 0){
break;
}
}
return result;
}
/**
* @param read
* @return
* @throws Exception
*/
private static String getTextByBufferedImage(BufferedImage read) throws Exception {
//二值化、去噪
BufferedImage img = removeBackgroud(read);
//分割图片
List<BufferedImage> listImg = splitImage(img);
//加载训练集图库
Map<BufferedImage, String> map = loadTrainData();
StringBuilder result = new StringBuilder();
//循环匹配单个图片
for (BufferedImage bi : listImg) {
result.append(getSingleCharOcr(bi, map));
}
return result.toString();
}
/**
* 根据文件路径得到验证码
*
* @param fileStr 文件路劲+文件名
* @return
* @throws Exception
*/
public static String getTextByFilePath(String fileStr) throws Exception {
File file = new File(fileStr);
BufferedImage read = ImageIO.read(file);
return getTextByBufferedImage(read);
}
/**
* 根据图片Url地址得到验证码
*
* @param urlStr
* @return
* @throws Exception
*/
public static String getTextByImageUrl(String urlStr) throws Exception {
URL url = new URL(urlStr);
BufferedImage read = ImageIO.read(url);
return getTextByBufferedImage(read);
}
/**
* 通过Base64编码得到验证码
*
* @param base64Text
* @return
* @throws Exception
*/
public static String getTextByBase64(String base64Text) throws Exception {
byte[] decode = Base64.decode(base64Text);
BufferedImage read = ImageIO.read(new ByteInputStream(decode, decode.length));
return getTextByBufferedImage(read);
}
/**
* 图片下载
*/
public static void downloadImage() {
CloseableHttpClient httpClient = HttpClientBuilder.create().build();
HttpGet httpGet = new HttpGet("http://iir.circ.gov.cn/web/servlet/ValidateCode");
httpGet.addHeader("Host", "game.tom.com");
httpGet.addHeader("User-Agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.94 Safari/537.36");
for (int i = 0; i < 30; i++) {
try {
CloseableHttpResponse execute = httpClient.execute(httpGet);
StatusLine statusLine = execute.getStatusLine();
int statusCode = statusLine.getStatusCode();
if (statusCode != HttpStatus.SC_OK) {
System.err.println("Method failed: " + statusLine);
}
InputStream inputStream = execute.getEntity().getContent();
FileOutputStream outputStream = new FileOutputStream(new File(dirPath + "temp/" + i + ".jpg"));
byte[] buff = new byte[1024];
int len = 0;
while((len = inputStream.read(buff, 0, 1024)) != -1){
outputStream.write(buff, 0, len);
}
inputStream.close();
outputStream.close();
// 读取内容
System.out.println(i + "OK!");
} catch (Exception e) {
e.printStackTrace();
} finally {
// 释放连接
httpGet.releaseConnection();
}
}
}
/**
* 训练数据
* @throws Exception
*/
public static void trainData() throws Exception {
File dir = new File(dirPath + "temp");
File[] files = dir.listFiles();
for (File file : files) {
//图片预处理 二值化、去噪
BufferedImage img = removeBackgroud(ImageIO.read(file));
//图片分割
List<BufferedImage> listImg = splitImage(img);
if (listImg.size() == 4) {
for (int j = 0; j < listImg.size(); ++j) {
ImageIO.write(listImg.get(j), "JPG", new File(dirPath + "train/" + file.getName().charAt(j) + "-" + (index++) + ".jpg"));
}
}
}
}
public static void writeImgByBase64(String base64Str) throws Base64DecodingException, IOException {
byte[] decode = Base64.decode(base64Str);
BufferedImage read = ImageIO.read(new ByteInputStream(decode, decode.length));
String name = UUID.randomUUID().toString().replaceAll("-", "") + ".jpg";
ImageIO.write(read, "JPG", new File(dirPath + "tmp/" + name));
}
public static void writeImgByBase64(String base64Str,String fileName) throws Base64DecodingException, IOException {
byte[] decode = Base64.decode(base64Str);
BufferedImage read = ImageIO.read(new ByteInputStream(decode, decode.length));
ImageIO.write(read, "JPG", new File(dirPath + "tmp/" + fileName + ".jpg"));
}
/**
* @param args
* @throws Exception
*/
public static void main(String[] args) throws Exception {
//downloadImage();//下载图片-保监会
//trainData();//训练图片
//String textUrl = getTextByImageUrl("http://iir.circ.gov.cn/web/servlet/ValidateCode?time=123");//保监会
//String textUrl2 = getTextByImageUrl("http://chexian.axatp.com/getAdditionNo.do?type=policy");//天平保单查询
//String text = getTextByImageFileUrl(dirPath + "temp/5xY5.jpg");
String base64Text = "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAYEBQYFBAYGBQYHBwYIChAKCgkJChQODwwQFxQYGBcU
" +
"FhYaHSUfGhsjHBYWICwgIyYnKSopGR8tMC0oMCUoKSj/2wBDAQcHBwoIChMKChMoGhYaKCgoKCgo
" +
"KCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCj/wAARCAAeAFoDASIA
" +
"AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA
" +
"AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3
" +
"ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm
" +
"p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA
" +
"AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx
" +
"BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK
" +
"U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3
" +
"uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD0HTNP
" +
"s3020Z7S3ZmhQkmNSSdo9qnl0nTpVCy6faOoYMA0KkZBBB6dQQCPcVl3VjpWu+C7Wz1xA2m3cNuG
" +
"SZ2hLElCinlWBL7Rjg549q8Q1/wxpE/xM0/w38NT/Zt9Bua+1G3kuHazwGDjzPMIPB2kbRhtql/m
" +
"YKAfQ39m2P8Az5W3/fpf8KP7Nsf+fK2/79L/AIVarz/4reNLDwvLothrFh9q03VpWS5kMzIIo0aP
" +
"cWVVJkXD8p0YAqchiKAO2/s2x/58rb/v0v8AhR/Ztj/z5W3/AH6X/CuBuPGvii4u9Ok0/wADarHp
" +
"txdLCkt1cLC53AqTPEI5HjjDZbdx91TnB2n0igDNS1sZbto4LTT5I4spORtLxSYRlUqF7q2eSCPl
" +
"4IbIsf2bY/8APlbf9+l/wry3x94k1Xw18SNNh1i+R/CWoqJYomggzFNDtYIrN0JkWP53IVRKcFSu
" +
"9ew+Hev6h4nsdQ1S5FqNLkvJY9MaGNlaW3RiokfcxOSRjG1SNpOORgA17zTNLjiu57+K0Fj5OJUn
" +
"ijEKKNxZiSvQg85JGFHA5zO2n232hAun2RgKsWcqAwbI2gLtwQRuycjGBwc8TfaPLn8u6aCLzZfL
" +
"th5uWl+TceCBhuH4GflXOeoHg/gDw1H8WdL8ReIfFk3n6lNK1lZFd6pY7Y9wKKHAZQZF+U/3SSSW
" +
"JoA9yXSNPW4eYWkO91VCCuVwCSML0B+Y5IGTxnOBjgdTVU1K7VFCqszgADAA3GpPgf4rn174fRXG
" +
"t3Gbi0ujYNczyDMx+TZk4HzHzFTuWIzkk03Vv+Qre/8AXZ//AEI0AaHjfXtV0bwIP+Eb0++vNZeG
" +
"COHyLN5lj3g5c4GDgI3rhim4YYZ4X4da5ZeDfDl0mvab4t0+8vmafUdcu9LwkcrDA+c7mIDHC7lb
" +
"LMSQAxA9OsfE1nBZW8LxXBaONUJCrjIGPWnN4nszcJIPtoRVZTEETaxJGGPfIwQMED5jkHjAB0Es
" +
"bO8LLM8YRtzKoXEg2kbWyCcZIPGDlRzjIPlfxm0S61jxf8P/ACtMnv7GK+b7XttzLGkZkgz5nBAU
" +
"gN14wDXUWPiNI90ksEUU0t1JJOYYM+bH8yxZO4Yk2CHcTkfKQBjBElx4g09LGWOys5lcMZ0jRvIV
" +
"5d3mfMyHIDPy3Bzk5DZIIB0kTfaJVnjknWNPMiMTR7AzBgNx3Lu42nBB2kNnkbSLFc//AMJXY/8A
" +
"PK5/75X/ABo/4Sux/wCeVz/3yv8AjQB5n8druXxVZy6Botq8n9kK+q6jdSZRLdY0lURkEZ3vyV6Z
" +
"G1hlSWHcfB/xHF4m8BadcIiRz2qizuI40CqskYA4AVVAKlWwowN2O1Ry634Z0mVr+PRliuJrqMvL
" +
"DaxLI0sjGMOTkEn962T1wzepyeHbrQtB+2HT7Frb7VL5jx20flw8cLti3lVbaFDFQNxGSOgAB3Fe
" +
"H+HH1z4WxeJNCt/D2q6rbyStd6Rc2lq1yjFlKgTspXGNkeQAD949Cpr0yXxPZu8LL9tjCNuZVRMS
" +
"DaRtbOTjJB4wcqOcZBk/4Sux/wCeVz/3yv8AjQBj/BzwnP4O8Ew2V/xf3ErXVygcOsbsAAoIHZVX
" +
"PX5t2CRis3Vv+Qre/wDXZ/8A0I11X/CV2P8Azyuf++V/xrkb6VZ724mQELJIzgHrgnNAH//Z";
String base64Result = getTextByBase64(base64Text);
System.out.println(base64Result);
writeImgByBase64(base64Text,base64Result);//生成图片
}
}
1. 新建3个文件夹指向代码中的文件地址
2.result 文件用来保存识别结果
3.temp 中的数据需手动设置
4.训练后的单个字符，用来匹配查找
执行后结果
trainData();//训练图片
