if (miniMatcher.matches() && miniMatcher.group("suffix") == null) {
            logger.info("deep dive into jpeg file {}", file);
            readImageStopWatcher.resume();
            BufferedImage image = ImageIO.read(file);
            readImageStopWatcher.suspend();
            int x = image.getWidth();
            int y = image.getHeight();

[INFO ] deep dive into jpeg file d:\www\more.jpg
[INFO ] centroid : [0.014503958111282333, 0.3971523133232788, 0.7814258647392994]
[INFO ] centroid : [0.9016215016768606, 0.7777823230018119, 0.518393124910854]
[INFO ] centroid : [0.13086001016253684, 0.20413363821139488, 0.05828304340026354]
[INFO ] centroid : [0.35836446218671053, 0.5249663996686114, 0.5807036415462928]

  public List<CentroidCluster> clusterize() {
        // Euclidian distance
        // TODO: Implement R:G:B color ratio
        DistanceMeasure distance = new EuclideanDistance();

        KMeansPlusPlusClusterer kMeansPlusPlusClusterer = new KMeansPlusPlusClusterer(clusters, maxIterations, distance);
        // Generate n clusters
        Collection<DoublePoint> points = new ArrayList();
        for (int y = 0; y < bufferedImage.getHeight(); y++) {
            for (int x = 0; x < bufferedImage.getWidth(); x++) {
                int rgb = bufferedImage.getRGB(x, y);
                DoublePoint doublePoint = new DoublePoint(new double[]{
                        ImageUtils.getRPixel(rgb) / 255.0,
                        ImageUtils.getGPixel(rgb) / 255.0,
                        ImageUtils.getBPixel(rgb) / 255.0,
                });
                points.add(doublePoint);
            }
        }
        // Find most popular cluster

        List<CentroidCluster> centroidClusters = kMeansPlusPlusClusterer.cluster(points);

        centroidClusters.forEach((item) -> {
            logger.info("centroid : {}", item.getCenter());
        });

        return centroidClusters;
    }

    public BufferedImage generateClusteredBars(BufferedImage original, List<CentroidCluster> clusters) {
        int x = original.getWidth();
        int y = original.getHeight();
        BufferedImage bars = new BufferedImage(x, y, BufferedImage.TYPE_INT_RGB);
        Graphics graphics = bars.getGraphics();
        int barsCnt = clusters.size();
        int barHeight = y / barsCnt;
        for (int i = 0; i < barsCnt; i++) {
            CentroidCluster cluster = clusters.get(i);
            Clusterable center = cluster.getCenter();
            graphics.setColor(new Color(
                    (float) center.getPoint()[0],
                    (float) center.getPoint()[1],
                    (float) center.getPoint()[2]));
            graphics.fillRect(0, i * barHeight, x, barHeight);
        }
        return bars;
    }