1.老规矩，先上图
要破解类似这样的验证码：
拆分后结果：
然后去匹配，得到结果。
2.拆分图片
拿到图片后，首先把图片中我们需要的部分截取出来。
具体的做法是，创建一个的和图片像素相同的一个代表权重的二维数组，遍历图片的每个像素点，如果接近白色，就标记为1，否则标记为0；
然后遍历这个二维数据，如果一个竖排都1，说明是空白列，直到第一次遇到不全为1一列，记住列的下标作为起始值，再次遇到全为1的，记住下标作为结束值，然后从起始列到结束列截取图片，依次类推。
//分割图片
private java.util.List<BufferedImage> splitImage(BufferedImage originImg)
throws Exception {
java.util.List<BufferedImage> subImgList = new ArrayList<>();
int height = originImg.getHeight();
int[][] weight = getImgWeight(originImg);
int start = 0;
int end = 0;
boolean isStartReady = false;
boolean isEndReady = false;
for (int i = 0; i < weight.length; i++) {
boolean isBlank = isBlankArr(weight[i]);
if (isBlank) {
if (isStartReady && !isEndReady) {
end = i;
isEndReady = true;
}
} else {
if (!isStartReady) {
start = i;
isStartReady = true;
}
}
if (isStartReady && isEndReady) {
subImgList.add(originImg.getSubimage(start, 0, end - start, height));
isStartReady = false;
isEndReady = false;
}
}
return subImgList;
}
//颜色是否为空白
private boolean isBlank(int colorInt) {
Color color = new Color(colorInt);
return color.getRed() + color.getGreen() + color.getBlue() > 600;
}
//数组是不是全空白
private boolean isBlankArr(int[] arr) {
boolean isBlank = true;
for (int value : arr) {
if (value == 0) {
isBlank = false;
break;
}
}
return isBlank;
}
//获取图片权重数据
private int[][] getImgWeight(BufferedImage img) {
int width = img.getWidth();
int height = img.getHeight();
int[][] weight = new int[width][height];
for (int x = 0; x < width; ++x) {
for (int y = 0; y < height; ++y) {
if (isBlank(img.getRGB(x, y))) {
weight[x][y] = 1;
}
}
}
return weight;
}
3.与拆分好的图片进行比较
拆分好的图片后，把拆分好的图片再次计算它的权重二维数据，加载之前准备好的"已知值的图片"，也计算权重数组。
然后对比两个二维数组，如果大部分都匹配，就确定了值。
如果没有找到匹配的，就把图片保存下来，人工识别后放入已知值的图片组。
//分析识别
private String realize(java.util.List<BufferedImage> imgList) {
String resultStr = "";
for (BufferedImage img : imgList) {
String key = getKey(Global.trainedMap, img);
if (key == null) {
String noTrainedKey = getKey(Global.noTrainedMap, img);
if(noTrainedKey == null){
try {
ImageIO.write(img, "JPG", new File(Global.LIB_NO + File.separator + UUID.randomUUID() + ".jpg"));
} catch (IOException e) {
e.printStackTrace();
}
}
} else {
resultStr += key;
}
}
return resultStr;
}
//获取已知值
private String getKey(Map<String, BufferedImage> map, BufferedImage img){
String resultStr = null;
Set<Map.Entry<String, BufferedImage>> entrySet = map.entrySet();
for (Map.Entry<String, BufferedImage> one : entrySet) {
if (isSimilarity(img, one.getValue())) {
resultStr = one.getKey();
break;
}
}
return resultStr;
}
//是否相似
private boolean isSimilarity(BufferedImage imageA, BufferedImage imageB) {
int widthA = imageA.getWidth();
int widthB = imageB.getWidth();
int heightA = imageA.getHeight();
int heightB = imageB.getHeight();
if (widthA != widthB || heightA != heightB) {
return false;
} else {
int[][] weightA = getImgWeight(imageA);
int[][] weightB = getImgWeight(imageB);
int count = 0;
for (int i = 0; i < widthA; i++) {
for (int j = 0; j < heightB; j++) {
if (weightA[i][j] != weightB[i][j]) {
count++;
}
}
}
if ((double) count / (widthA * widthB) > (1 - Global.SIMILARITY)) {
return false;
} else {
return true;
}
}
}
4.完整代码
import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
public class Global {
public static final String LIB_PATH = "C:/lib";
public static final String LIB_NO = "C:/no";
public static final double SIMILARITY = 0.9;
public static Map<String, BufferedImage> trainedMap;
public static Map<String, BufferedImage> noTrainedMap = new HashMap<>();
static {
trainedMap = getMap(LIB_PATH);
noTrainedMap = getMap(LIB_NO);
}
private static Map<String, BufferedImage> getMap(String path) {
Map<String, BufferedImage> map = new HashMap<>();
File parentFile = new File(path);
for (String filePath : parentFile.list()) {
File file = new File(path + File.separator + filePath);
String fileName = file.getName();
String key = fileName.substring(0,fileName.indexOf(".")).trim();
try {
map.put(key, ImageIO.read(file));
} catch (IOException e) {
e.printStackTrace();
}
}
return map;
}
}
import javax.imageio.ImageIO;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.*;
/**
* 识别验证码
*/
public class ImageProcess {
private String imgPath;
public ImageProcess(String imgPath) {
this.imgPath = imgPath;
}
public String getResult() {
java.util.List<BufferedImage> imgList = null;
try {
BufferedImage img = ImageIO.read(new File(imgPath));
imgList = splitImage(img);
} catch (IOException e) {
e.printStackTrace();
} catch (Exception e) {
e.printStackTrace();
}
return realize(imgList);
}
//分析识别
private String realize(java.util.List<BufferedImage> imgList) {
String resultStr = "";
for (BufferedImage img : imgList) {
String key = getKey(Global.trainedMap, img);
if (key == null) {
String noTrainedKey = getKey(Global.noTrainedMap, img);
if(noTrainedKey == null){
try {
ImageIO.write(img, "JPG", new File(Global.LIB_NO + File.separator + UUID.randomUUID() + ".jpg"));
} catch (IOException e) {
e.printStackTrace();
}
}
} else {
resultStr += key;
}
}
return resultStr;
}
//获取已知值
private String getKey(Map<String, BufferedImage> map, BufferedImage img){
String resultStr = null;
Set<Map.Entry<String, BufferedImage>> entrySet = map.entrySet();
for (Map.Entry<String, BufferedImage> one : entrySet) {
if (isSimilarity(img, one.getValue())) {
resultStr = one.getKey();
break;
}
}
return resultStr;
}
//是否相似
private boolean isSimilarity(BufferedImage imageA, BufferedImage imageB) {
int widthA = imageA.getWidth();
int widthB = imageB.getWidth();
int heightA = imageA.getHeight();
int heightB = imageB.getHeight();
if (widthA != widthB || heightA != heightB) {
return false;
} else {
int[][] weightA = getImgWeight(imageA);
int[][] weightB = getImgWeight(imageB);
int count = 0;
for (int i = 0; i < widthA; i++) {
for (int j = 0; j < heightB; j++) {
if (weightA[i][j] != weightB[i][j]) {
count++;
}
}
}
if ((double) count / (widthA * widthB) > (1 - Global.SIMILARITY)) {
return false;
} else {
return true;
}
}
}
//分割图片
private java.util.List<BufferedImage> splitImage(BufferedImage originImg)
throws Exception {
java.util.List<BufferedImage> subImgList = new ArrayList<>();
int height = originImg.getHeight();
int[][] weight = getImgWeight(originImg);
int start = 0;
int end = 0;
boolean isStartReady = false;
boolean isEndReady = false;
for (int i = 0; i < weight.length; i++) {
boolean isBlank = isBlankArr(weight[i]);
if (isBlank) {
if (isStartReady && !isEndReady) {
end = i;
isEndReady = true;
}
} else {
if (!isStartReady) {
start = i;
isStartReady = true;
}
}
if (isStartReady && isEndReady) {
subImgList.add(originImg.getSubimage(start, 0, end - start, height));
isStartReady = false;
isEndReady = false;
}
}
return subImgList;
}
//颜色是否为空白
private boolean isBlank(int colorInt) {
Color color = new Color(colorInt);
return color.getRed() + color.getGreen() + color.getBlue() > 600;
}
//数组是不是全空白
private boolean isBlankArr(int[] arr) {
boolean isBlank = true;
for (int value : arr) {
if (value == 0) {
isBlank = false;
break;
}
}
return isBlank;
}
//获取图片权重数据
private int[][] getImgWeight(BufferedImage img) {
int width = img.getWidth();
int height = img.getHeight();
int[][] weight = new int[width][height];
for (int x = 0; x < width; ++x) {
for (int y = 0; y < height; ++y) {
if (isBlank(img.getRGB(x, y))) {
weight[x][y] = 1;
}
}
}
return weight;
}
public static void main(String[] args) throws Exception {
String result = new ImageProcess("C:/login.jpg").getResult();
System.out.println(result);
}
}