java 图像灰度化与二值化

转载：http://www.chinasb.org/archives/2013/01/5053.shtml

  1:  package org.chinasb.client;
  2:
  3:  import java.awt.Color;
  4:  import java.awt.image.BufferedImage;
  5:  import java.io.File;
  6:  import java.io.IOException;
  7:
  8:  import javax.imageio.ImageIO;
  9:
 10:  public class BinaryTest {
 11:
 12:      public static void main(String[] args) throws IOException {
 13:          BufferedImage bufferedImage = ImageIO.read(new File("D:/passCodeAction.jpg"));
 14:          int h = bufferedImage.getHeight();
 15:          int w = bufferedImage.getWidth();
 16:
 17:          // 灰度化
 18:          int[][] gray = new int[w][h];
 19:          for (int x = 0; x < w; x++) {
 20:              for (int y = 0; y < h; y++) {
 21:                  int argb = bufferedImage.getRGB(x, y);
 22:                  int r = (argb >> 16) & 0xFF;
 23:                  int g = (argb >> 8) & 0xFF;
 24:                  int b = (argb >> 0) & 0xFF;
 25:                  int grayPixel = (int) ((b * 29 + g * 150 + r * 77 + 128) >> 8);
 26:                  gray[x][y] = grayPixel;
 27:              }
 28:          }
 29:
 30:          // 二值化
 31:          int threshold = ostu(gray, w, h);
 32:          BufferedImage binaryBufferedImage = new BufferedImage(w, h, BufferedImage.TYPE_BYTE_BINARY);
 33:          for (int x = 0; x < w; x++) {
 34:              for (int y = 0; y < h; y++) {
 35:                  if (gray[x][y] > threshold) {
 36:                      gray[x][y] |= 0x00FFFF;
 37:                  } else {
 38:                      gray[x][y] &= 0xFF0000;
 39:                  }
 40:                  binaryBufferedImage.setRGB(x, y, gray[x][y]);
 41:              }
 42:          }
 43:
 44:          // 矩阵打印
 45:          for (int y = 0; y < h; y++) {
 46:              for (int x = 0; x < w; x++) {
 47:                  if (isBlack(binaryBufferedImage.getRGB(x, y))) {
 48:                      System.out.print("*");
 49:                  } else {
 50:                      System.out.print(" ");
 51:                  }
 52:              }
 53:              System.out.println();
 54:          }
 55:
 56:          ImageIO.write(binaryBufferedImage, "jpg", new File("D:/code.jpg"));
 57:      }
 58:
 59:      public static boolean isBlack(int colorInt) {
 60:          Color color = new Color(colorInt);
 61:          if (color.getRed() + color.getGreen() + color.getBlue() <= 300) {
 62:              return true;
 63:          }
 64:          return false;
 65:      }
 66:
 67:      public static boolean isWhite(int colorInt) {
 68:          Color color = new Color(colorInt);
 69:          if (color.getRed() + color.getGreen() + color.getBlue() > 300) {
 70:              return true;
 71:          }
 72:          return false;
 73:      }
 74:
 75:      public static int isBlackOrWhite(int colorInt) {
 76:          if (getColorBright(colorInt) < 30 || getColorBright(colorInt) > 730) {
 77:              return 1;
 78:          }
 79:          return 0;
 80:      }
 81:
 82:      public static int getColorBright(int colorInt) {
 83:          Color color = new Color(colorInt);
 84:          return color.getRed() + color.getGreen() + color.getBlue();
 85:      }
 86:
 87:      public static int ostu(int[][] gray, int w, int h) {
 88:          int[] histData = new int[w * h];
 89:          // Calculate histogram
 90:          for (int x = 0; x < w; x++) {
 91:              for (int y = 0; y < h; y++) {
 92:                  int red = 0xFF & gray[x][y];
 93:                  histData[red]++;
 94:              }
 95:          }
 96:
 97:          // Total number of pixels
 98:          int total = w * h;
 99:
100:          float sum = 0;
101:          for (int t = 0; t < 256; t++)
102:              sum += t * histData[t];
103:
104:          float sumB = 0;
105:          int wB = 0;
106:          int wF = 0;
107:
108:          float varMax = 0;
109:          int threshold = 0;
110:
111:          for (int t = 0; t < 256; t++) {
112:              wB += histData[t]; // Weight Background
113:              if (wB == 0)
114:                  continue;
115:
116:              wF = total - wB; // Weight Foreground
117:              if (wF == 0)
118:                  break;
119:
120:              sumB += (float) (t * histData[t]);
121:
122:              float mB = sumB / wB; // Mean Background
123:              float mF = (sum - sumB) / wF; // Mean Foreground
124:
125:              // Calculate Between Class Variance
126:              float varBetween = (float) wB * (float) wF * (mB - mF) * (mB - mF);
127:
128:              // Check if new maximum found
129:              if (varBetween > varMax) {
130:                  varMax = varBetween;
131:                  threshold = t;
132:              }
133:          }
134:
135:          return threshold;
136:      }
137:  }

 

效果