Java基于直方图应用的相似图片识别实例

public void setGreenBinCount(int greenBinCount) { 
  this.greenBins = greenBinCount; 
} 
 
public void setBlueBinCount(int blueBinCount) { 
  this.blueBins = blueBinCount; 
} 
 
public float[] filter(BufferedImage src, BufferedImage dest) { 
  int width = src.getWidth(); 
    int height = src.getHeight(); 
     
    int[] inPixels = new int[width*height]; 
    float[] histogramData = new float[redBins * greenBins * blueBins]; 
    getRGB( src, 0, 0, width, height, inPixels ); 
    int index = 0; 
    int redIdx = 0, greenIdx = 0, blueIdx = 0; 
    int singleIndex = 0; 
    float total = 0; 
    for(int row=0; row<height; row++) { 
    int ta = 0, tr = 0, tg = 0, tb = 0; 
    for(int col=0; col<width; col++) { 
      index = row * width + col; 
      ta = (inPixels[index] >> 24) & 0xff; 
        tr = (inPixels[index] >> 16) & 0xff; 
        tg = (inPixels[index] >> 8) & 0xff; 
        tb = inPixels[index] & 0xff; 
        redIdx = (int)getBinIndex(redBins, tr, 255); 
        greenIdx = (int)getBinIndex(greenBins, tg, 255); 
        blueIdx = (int)getBinIndex(blueBins, tb, 255); 
        singleIndex = redIdx + greenIdx * redBins + blueIdx * redBins * greenBins; 
        histogramData[singleIndex] += 1; 
        total += 1; 
    } 
    } 
     
    // start to normalize the histogram data 
    for (int i = 0; i < histogramData.length; i++) 
    { 
    histogramData[i] = histogramData[i] / total; 
    } 
     
    return histogramData; 
} 

/** 
 * Bhattacharyya Coefficient 
 * http://www.cse.yorku.ca/~kosta/CompVis_Notes/bhattacharyya.pdf 
 * 
 * @return 
 */ 
public double modelMatch() { 
  HistogramFilter hfilter = new HistogramFilter(); 
  float[] sourceData = hfilter.filter(sourceImage, null); 
  float[] candidateData = hfilter.filter(candidateImage, null); 
  double[] mixedData = new double[sourceData.length]; 
  for(int i=0; i<sourceData.length; i++ ) { 
    mixedData[i] = Math.sqrt(sourceData[i] * candidateData[i]); 
  } 
   
  // The values of Bhattacharyya Coefficient ranges from 0 to 1, 
  double similarity = 0; 
  for(int i=0; i<mixedData.length; i++ ) { 
    similarity += mixedData[i]; 
  } 
   
  // The degree of similarity 
  return similarity; 
}