按照索引的细化提取骨架算法的java实现

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();
        }

    }

}