近期研究验证码识别,也就看了一些图像识别的资料,其中一种字体细化提取骨架的算法网上没有java版的实现,所以就选取了一个python实现版本进行java代码的改写..
python版实现的地址:
http://www.cnblogs.com/xianglan/archive/2011/01/01/1923779.html
由于我不是很懂python语法,也是直接去的w3c看的教程,为此还掉进了一个坑..详见:
http://www.cnblogs.com/chyu/p/4335950.html
由于我对图像处理这里不是很在行,python也是临时看的,故这种细化提取骨架的算法也就是直接移植原代码,并没做什么优化之类..代码很粗糙..
package com.ocr.imgocr; import java.awt.Color;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException; import javax.imageio.ImageIO; public class Thin {
//索引数组
private static Integer[] array = {0,0,1,1,0,0,1,1,1,1,0,1,1,1,0,1,
1,1,0,0,1,1,1,1,0,0,0,0,0,0,0,1,
0,0,1,1,0,0,1,1,1,1,0,1,1,1,0,1,
1,1,0,0,1,1,1,1,0,0,0,0,0,0,0,1,
1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
1,1,0,0,1,1,0,0,1,1,0,1,1,1,0,1,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,1,1,0,0,1,1,1,1,0,1,1,1,0,1,
1,1,0,0,1,1,1,1,0,0,0,0,0,0,0,1,
0,0,1,1,0,0,1,1,1,1,0,1,1,1,0,1,
1,1,0,0,1,1,1,1,0,0,0,0,0,0,0,0,
1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,
1,1,0,0,1,1,1,1,0,0,0,0,0,0,0,0,
1,1,0,0,1,1,0,0,1,1,0,1,1,1,0,0,
1,1,0,0,1,1,1,0,1,1,0,0,1,0,0,0}; public static boolean isWhite(int colorInt) {
Color color = new Color(colorInt);
if (color.getRed() + color.getGreen() + color.getBlue() > 400) {
return true;
}
return false;
} public static BufferedImage VThin(BufferedImage image,Integer[] array){
int h = image.getHeight();
int w = image.getWidth();
int NEXT = 1;
for(int i=0;i<h;i++){
for(int j=0;j<w;j++){
if (NEXT == 0){
NEXT = 1;
}else{
int M ;
if( 0<j&&j<w-1){
if(isBlack(image.getRGB(j-1,i))&&isBlack(image.getRGB(j,i))&&isBlack(image.getRGB(j+1,i))){
M=0;
}else{
M=1;
}
}else {
M = 1;
}
if(isBlack(image.getRGB(j,i))&&M!=0){
int[] a = {0,0,0,0,0,0,0,0,0};
for(int k=0;k<3;k++){
for(int l=0;l<3;l++){
if ((-1<(i-1+k)&&(i-1+k)<h) && (-1<(j-1+l)&&(j-1+l)<w) && isWhite(image.getRGB(j-1+l,i-1+k))){
a[k*3+l] = 1;
}
}
}
int sum = a[0]*1+a[1]*2+a[2]*4+a[3]*8+a[5]*16+a[6]*32+a[7]*64+a[8]*128;
if(array[sum]==0){
image.setRGB(j, i, Color.black.getRGB());
}else{
image.setRGB(j, i, Color.white.getRGB());
}
if (array[sum] == 1){
NEXT = 0;
}
}
}
}
}
return image;
} public static BufferedImage HThin(BufferedImage image,Integer[] array){
int h = image.getHeight();
int w = image.getWidth();
int NEXT = 1;
for(int j=0;j<w;j++){
for(int i=0;i<h;i++){
if (NEXT == 0){
NEXT = 1;
}else{
int M;
if(0<i&&i<h-1){
if(isBlack(image.getRGB(j,i-1))&&isBlack(image.getRGB(j,i))&&isBlack(image.getRGB(j,i+1))){
M=0;
}else{
M=1;
}
}else{
M = 1;
}
if (isBlack(image.getRGB(j,i)) && M != 0){
int[] a = {0,0,0,0,0,0,0,0,0};
for(int k=0;k<3;k++){
for(int l=0;l<3;l++){
if ((-1<(i-1+k)&&(i-1+k)<h) && (-1<(j-1+l)&&(j-1+l)<w )&& isWhite(image.getRGB(j-1+l,i-1+k))){
a[k*3+l] = 1;
}
}
}
int sum = a[0]*1+a[1]*2+a[2]*4+a[3]*8+a[5]*16+a[6]*32+a[7]*64+a[8]*128;
if(array[sum]==0){
image.setRGB(j, i, Color.black.getRGB());
}else{
image.setRGB(j, i, Color.white.getRGB());
}
if (array[sum] == 1){
NEXT = 0;
}
}
}
}
}
return image;
} public static BufferedImage Xihua(BufferedImage image,Integer[] array){
int num=10;
BufferedImage iXihua = image;
for(int i=0;i<num;i++){
VThin(iXihua,array);
HThin(iXihua,array);
}
return iXihua;
} public static BufferedImage Two(BufferedImage image){
int w = image.getWidth();
int h = image.getHeight();
BufferedImage iTwo = image;
for(int i=0;i<h;i++){
for(int j=0;j<w;j++){
if(isBlack(image.getRGB(j,i))){
iTwo.setRGB(j, i, Color.BLACK.getRGB());
}else{
iTwo.setRGB(j, i, Color.WHITE.getRGB());
}
}
}
return iTwo;
} public static boolean isBlack(int colorInt) {
Color color = new Color(colorInt);
if (color.getRed() + color.getGreen() + color.getBlue() <= 400) {
return true;
}
return false;
} public static void main(String[] args) {
try {
//原始图片路径
BufferedImage image = ImageIO.read(new File("image"+File.separator+"0.jpg"));
//二值化
BufferedImage iTwo = Two(image);
ImageIO.write(iTwo, "jpg", new File("image"+File.separator+"two.jpg"));
//细化
BufferedImage iThin = Xihua(image,array);
ImageIO.write(iThin, "jpg", new File("image"+File.separator+"thin.jpg")); } catch (IOException e) {
e.printStackTrace();
} } }