App基于手机壳颜色换肤？先尝试一下用 KMeans 来提取图像中的主色

    public List<Scalar> extract(ColorProcessor processor) {
        // initialization the pixel data
        int width = processor.getWidth();
        int height = processor.getHeight();
        byte[] R = processor.getRed();
        byte[] G = processor.getGreen();
        byte[] B = processor.getBlue();
        
        //Create random points to use a the cluster center
        Random random = new Random();
        int index = 0;
        for (int i = 0; i < numOfCluster; i++)
        {
            int randomNumber1 = random.nextInt(width);
            int randomNumber2 = random.nextInt(height);
            index = randomNumber2 * width + randomNumber1;
            ClusterCenter cc = new ClusterCenter(randomNumber1, randomNumber2, R[index]&0xff, G[index]&0xff, B[index]&0xff);
            cc.cIndex = i;
            clusterCenterList.add(cc); 
        }
        
        // create all cluster point
        for (int row = 0; row < height; ++row)
        {
            for (int col = 0; col < width; ++col)
            {
                index = row * width + col;
                pointList.add(new ClusterPoint(row, col, R[index]&0xff, G[index]&0xff, B[index]&0xff));

            }
        }
        
        // initialize the clusters for each point
        double[] clusterDisValues = new double[clusterCenterList.size()];
        for(int i=0; i<pointList.size(); i++)
        {
            for(int j=0; j<clusterCenterList.size(); j++)
            {
                clusterDisValues[j] = calculateEuclideanDistance(pointList.get(i), clusterCenterList.get(j));
            }
            pointList.get(i).clusterIndex = (getCloserCluster(clusterDisValues));
        }
        
        // calculate the old summary
        // assign the points to cluster center
        // calculate the new cluster center
        // computation the delta value
        // stop condition--
        double[][] oldClusterCenterColors = reCalculateClusterCenters();
        int times = 10;
        while(true)
        {
            stepClusters();
            double[][] newClusterCenterColors = reCalculateClusterCenters();
            if(isStop(oldClusterCenterColors, newClusterCenterColors))
            {               
                break;
            } 
            else
            {
                oldClusterCenterColors = newClusterCenterColors;
            }
            if(times > 10) {
                break;
            }
            times++;
        }
        
        //update the result image
        List<Scalar> colors = new ArrayList<Scalar>();
        for(ClusterCenter cc : clusterCenterList) {
            
            colors.add(cc.color);
        }
        return colors;
    }

    private boolean isStop(double[][] oldClusterCenterColors, double[][] newClusterCenterColors) {
        boolean stop = false;
        for (int i = 0; i < oldClusterCenterColors.length; i++) {
            if (oldClusterCenterColors[i][0] == newClusterCenterColors[i][0] &&
                    oldClusterCenterColors[i][1] == newClusterCenterColors[i][1] &&
                    oldClusterCenterColors[i][2] == newClusterCenterColors[i][2]) {
                stop = true;
                break;
            }
        }
        return stop;
    }

    /**
     * update the cluster index by distance value
     */
    private void stepClusters() 
    {
        // initialize the clusters for each point
        double[] clusterDisValues = new double[clusterCenterList.size()];
        for(int i=0; i<pointList.size(); i++)
        {
            for(int j=0; j<clusterCenterList.size(); j++)
            {
                clusterDisValues[j] = calculateEuclideanDistance(pointList.get(i), clusterCenterList.get(j));
            }
            pointList.get(i).clusterIndex = (getCloserCluster(clusterDisValues));
        }
        
    }

    /**
     * using cluster color of each point to update cluster center color
     * 
     * @return
     */
    private double[][] reCalculateClusterCenters() {
        
        // clear the points now
        for(int i=0; i<clusterCenterList.size(); i++)
        {
             clusterCenterList.get(i).numOfPoints = 0;
        }
        
        // recalculate the sum and total of points for each cluster
        double[] redSums = new double[numOfCluster];
        double[] greenSum = new double[numOfCluster];
        double[] blueSum = new double[numOfCluster];
        for(int i=0; i<pointList.size(); i++)
        {
            int cIndex = (int)pointList.get(i).clusterIndex;
            clusterCenterList.get(cIndex).numOfPoints++;
            int tr = pointList.get(i).pixelColor.red;
            int tg = pointList.get(i).pixelColor.green;
            int tb = pointList.get(i).pixelColor.blue;
            redSums[cIndex] += tr;
            greenSum[cIndex] += tg;
            blueSum[cIndex] += tb;
        }
        
        double[][] oldClusterCentersColors = new double[clusterCenterList.size()][3];
        for(int i=0; i<clusterCenterList.size(); i++)
        {
            double sum  = clusterCenterList.get(i).numOfPoints;
            int cIndex = clusterCenterList.get(i).cIndex;
            int red = (int)(greenSum[cIndex]/sum);
            int green = (int)(greenSum[cIndex]/sum);
            int blue = (int)(blueSum[cIndex]/sum);
            clusterCenterList.get(i).color = new Scalar(red, green, blue);
            oldClusterCentersColors[i][0] = red;
            oldClusterCentersColors[i][0] = green;
            oldClusterCentersColors[i][0] = blue;
        }
        
        return oldClusterCentersColors;
    }
    
    

    /**
     * 
     * @param clusterDisValues
     * @return
     */
    private double getCloserCluster(double[] clusterDisValues)
    {
        double min = clusterDisValues[0];
        int clusterIndex = 0;
        for(int i=0; i<clusterDisValues.length; i++)
        {
            if(min > clusterDisValues[i])
            {
                min = clusterDisValues[i];
                clusterIndex = i;
            }
        }
        return clusterIndex;
    }

    /**
     *
     * @param p
     * @param c
     * @return distance value
     */
    private double calculateEuclideanDistance(ClusterPoint p, ClusterCenter c) 
    {
        int pr = p.pixelColor.red;
        int pg = p.pixelColor.green;
        int pb = p.pixelColor.blue;
        int cr = c.color.red;
        int cg = c.color.green;
        int cb = c.color.blue;
        return Math.sqrt(Math.pow((pr - cr), 2.0) + Math.pow((pg - cg), 2.0) + Math.pow((pb - cb), 2.0));
    }