convert RGB colorspace to Homochromy(Black/whit)
//
convert RGB colorspace to Homochromy(Black/whit)
static
public
int
ConvertRGBtoHomochromy(
int
x,
int
bw)
{
String rgbString = Integer.toHexString(x).toUpperCase(); if (rgbString.length()!=6)
{
return Integer.parseInt("000000", 16);
} String strR,strG,strB; strR = rgbString.substring(0, 2); strG = rgbString.substring(2, 4); strB = rgbString.substring(4, 6); int intR,intG,intB; intR = Integer.parseInt(strR, 16); intG = Integer.parseInt(strG, 16); intB = Integer.parseInt(strB, 16); //get lum value from RGB int y = (int)(0.299 * intR + 0.587 * intG + 0.114 * intB); if(y>bw) { y = 255; } else { y = 0; } String result = Integer.toHexString(y).toUpperCase()+ Integer.toHexString(y).toUpperCase() + Integer.toHexString(y).toUpperCase(); return Integer.parseInt(result, 16);
}
ColorModel cm =image.getColorModel();
if((image.getType()!=BufferedImage.TYPE_BYTE_BINARY)||(cm.getPixelSize()!=1)){
//BufferedImage grayImage=new BufferedImage(image.getWidth(),image.getHeight(),BufferedImage.TYPE_BYTE_BINARY);
//grayImage.getGraphics().drawImage(image,0,0,null);
WritableRaster raster =image.getRaster();
//image = grayImage;
DataBufferInt buffer=(DataBufferInt)raster.getDataBuffer();
int[] imgdata=(int[])buffer.getData();
for(int i=0; i<imgdata.length;i++)
{
imgdata[i] = ConvertRGBtoHomochromy(imgdata[i],190);
//i=0;
}
image.setData(raster);
//image = convert(image,BufferedImage.TYPE_BYTE_BINARY);
File jpgFile = new File("C:""Documents and Settings""ar""My Documents","afterbw.jpg");jpgFile.delete();
ImageIO.write(image, "jpg", jpgFile);
below code is how to get threshold value from image for convertor.
static
public
int
getThreshold(BufferedImage image)
{ int thresholdValue=1; // threshold int[] ihist = new int[256]; // int i, j, k; // various counters int n, n1, n2, gmin, gmax; double m1, m2, sum, csum, fmax, sb; // reset for(i=0;i<256;i++){ ihist[i] = 0; } gmin=255; gmax=0; for (i = 1; i < image.getWidth()-1 ; i++) { for (j = 1; j < image.getHeight()-1 ; j++) { //get gray value base on RGB value int cn = getGrayValue(image.getRGB(i, j)); ihist[cn]++; if(cn > gmax) gmax=cn; if(cn < gmin) gmin=cn; } } // set up everything sum = csum = 0.0; n = 0; for (k = 0; k <= 255; k++) { sum += (double) k * (double) ihist[k]; /* x*f(x) */ n += ihist[k]; /* f(x) */ } if (n==0) { // if n has no value, there is problems
return (60); } // do the otsu global thresholding method fmax = -1.0; n1 = 0; for (k = 0; k < 255; k++) { n1 += ihist[k]; if (n1==0) { continue; } n2 = n - n1; if (n2 == 0) { break; } csum += (double) k *ihist[k]; m1 = csum / n1; m2 = (sum - csum) / n2; sb = (double) n1 *(double) n2 *(m1 - m2) * (m1 - m2); /* bbg: note: can be optimized. */ if (sb > fmax) { fmax = sb; thresholdValue = k; } } // at this point we have our thresholding value return thresholdValue; }
and the orginal codes be changed:
int
thresholdValue
=
getThreshold(image);
for
(
int
i
=
0
; i
<
imgdata.length;i
++
)
{ //imgdata[i] = ConvertRGBtoGray(imgdata[i]); imgdata[i] = ConvertRGBtoHomochromy(imgdata[i],thresholdValue); //i=0; }
添加 edge detect ,用来找到边界去掉背景块
static
public
BufferedImage edgeDetect(BufferedImage img)
{ int w = img.getWidth(null); int h = img.getHeight(null); BufferedImage newImage = new BufferedImage(w,h,1); for (int y=0;y<h;y++) for (int x=0;x<w;x++){ int c=img.getRGB(x,y); newImage.setRGB(x,y,c); } int c,red,green,blue,avg,d=3; for (int y=0;y<h;y++) for (int x=0;x<w;x++){ c=img.getRGB(x,y); red=getRed(c); green=getGreen(c); blue=getBlue(c); avg=(red+green+blue)/d; newImage.setRGB(x,y,createRGB(avg,avg,avg)); } Kernel k = new Kernel(3, 3, new float[] { 0.0f, 1.0f, 0.0f, 1.0f, -4.0f, 1.0f, 0.0f, 1.0f, 0.0f }); ConvolveOp op = new ConvolveOp(k); BufferedImage img2 = op.filter(newImage, null); return img2; }
添加去杂点的处理方法：
static
private
int
getMiddleValue(
int
[] arrayValue)
{ int v; for(int i=0;i<=7;i++) { for(int j=0;j<=7;j++) { if (arrayValue[j]<arrayValue[j+1]) { v = arrayValue[j]; arrayValue[j] = arrayValue[j+1]; arrayValue[j+1] = v; } } } return arrayValue[5]; }
static
private
BufferedImage Opt(BufferedImage image)
{ int width = image.getWidth(); int height = image.getHeight(); int[] c = new int[9]; for(int i=1;i<width-1;i++) { for(int j=1;j<height-1;j++){ int cc = image.getRGB(i, j); c[0] = image.getRGB(i-1, j-1); c[1] = image.getRGB(i, j-1); c[2] = image.getRGB(i+1, j-1); c[3] = image.getRGB(i-1, j); c[4] = image.getRGB(i, j); c[5] = image.getRGB(i+1, j); c[6] = image.getRGB(i-1, j+1); c[7] = image.getRGB(i, j+1); c[8] = image.getRGB(i+1, j+1); cc = getMiddleValue(c); image.setRGB(i,j,cc); } } return image; }
更新edge detect 算法
static
public
int
[] apply_sobel(
int
[] src_1d,
int
width,
int
height,
double
sobscale,
float
offsetval)
{ int i_w = width; int i_h = height; int d_w = width; int d_h = height; int[] dest_1d = new int[d_w * d_h]; for(int i=0;i<src_1d.length;i++){ try { int a = src_1d[i] & 0x000000ff; int b = src_1d[i+ 1] & 0x000000ff; int c = src_1d[i+ 2] & 0x000000ff; int d = src_1d[i + i_w] & 0x000000ff; int e = src_1d[i + i_w + 2] & 0x000000ff; int f = src_1d[i + 2*i_w ] & 0x000000ff; int g = src_1d[i + 2*i_w + 1] & 0x000000ff; int h = src_1d[i + 2*i_w + 2] & 0x000000ff; int hor = (a+d+f) - (c+e+h); if (hor < 0) hor = -hor; int vert = (a+b+c) - (f+g+h); if (vert < 0) vert = -vert; short gc = (short) (sobscale * (hor + vert)); gc = (short) (gc + offsetval); if (gc > 255) gc = 255; dest_1d[i] = 0xff000000 | gc<<16 | gc<<8 | gc; //reached borders of image so goto next row //(see Convolution.java) if (((i+3)%i_w)==0) { dest_1d[i] = 0; dest_1d[i+1] = 0; dest_1d[i+2] = 0; i+=3; } } catch (ArrayIndexOutOfBoundsException e) {//if reached row boudary of image return. i = src_1d.length; } } return dest_1d; }