diff --git a/openbr/plugins/representation/gradienthistogram.cpp b/openbr/plugins/representation/gradienthistogram.cpp
deleted file mode 100644
index 0958032..0000000
--- a/openbr/plugins/representation/gradienthistogram.cpp
+++ /dev/null
@@ -1,145 +0,0 @@
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/highgui/highgui.hpp>
-
-#include <openbr/plugins/openbr_internal.h>
-#include <openbr/core/opencvutils.h>
-
-using namespace cv;
-
-namespace br
-{
-
-/*!
- * \ingroup representations
- * \brief Computes first order gradient histogram features using an integral image
- * \author Scott Klum \cite sklum
- */
-class GradientHistogramRepresentation : public Representation
-{
-    Q_OBJECT
-
-    Q_PROPERTY(int winWidth READ get_winWidth WRITE set_winWidth RESET reset_winWidth STORED false)
-    Q_PROPERTY(int winHeight READ get_winHeight WRITE set_winHeight RESET reset_winHeight STORED false)
-    Q_PROPERTY(int bins READ get_bins WRITE set_bins RESET reset_bins STORED false)
-    Q_PROPERTY(bool squareOnly READ get_squareOnly WRITE set_squareOnly RESET reset_squareOnly STORED false)
-    BR_PROPERTY(int, winWidth, 24)
-    BR_PROPERTY(int, winHeight, 24)
-    BR_PROPERTY(int, bins, 6)
-    BR_PROPERTY(bool, squareOnly, false)
-
-    void init()
-    {
-        if (features.isEmpty()) {
-            int dx, dy;
-            Size size = windowSize(&dx,&dy);
-
-            int width = size.width+dx, height = size.height+dy;
-
-            // Enumerate all possible rectangles
-            for (int x=0; x<width; x++)
-                for (int y=0; y<height; y++)
-                    for (int w=1; w < width-x; w++)
-                        for (int h=1; h < height-y; h++)
-                            if (!squareOnly || w == h)
-                                features.append(Rect(x,y,w,h));
-        }
-
-        qDebug() << "Number of Gradient Histogram features:" << features.size();
-    }
-
-    void preprocess(const Mat &src, Mat &dst) const
-    {
-        // Compute as is done in GradientTransform
-        Mat dx, dy, magnitude, angle;
-        Sobel(src, dx, CV_32F, 1, 0, CV_SCHARR);
-        Sobel(src, dy, CV_32F, 0, 1, CV_SCHARR);
-        cartToPolar(dx, dy, magnitude, angle, true);
-
-        const double floor = ((src.depth() == CV_32F) || (src.depth() == CV_64F)) ? -0.5 : 0;
-
-        Mat histogram;
-        angle.convertTo(histogram, bins > 256 ? CV_16U : CV_8U, bins/360., floor);
-
-        // Mask and compute integral image
-        std::vector<Mat> outputs;
-        for (int i=0; i<bins; i++) {
-            Mat output = (histogram == i)/255;
-            Mat integralImg;
-            integral(output, integralImg);
-            outputs.push_back(integralImg);
-        }
-
-        merge(outputs,dst);
-    }
-
-    /*  ___ ___
-     * |   |   |
-     * | A | B |
-     * |___|___|
-     * |   |   |
-     * | C | D |
-     * |___|___|
-     *
-     * 1, 2, 3 and 4 refer to the lower right corners of A, B, C, and D, respectively.
-     * Rectangle D can be computed as 4 + 1 - (2 + 3)
-     */
-
-    float evaluate(const Mat &image, int idx) const
-    {
-        // To which channel does idx belong?
-        const int index = idx % features.size();
-        const int channel = idx / features.size();
-
-        int dx, dy;
-        Size size = windowSize(&dx, &dy);
-
-        const int *ptr = image.ptr<int>();
-
-        int four = ptr[((features[index].y+features[index].height)*(size.height+dy)+(features[index].x+features[index].width))*bins+channel];
-        int one = ptr[(features[index].y*(size.height+dy)+features[index].x)*bins+channel];
-        int two = ptr[(features[index].y*(size.height+dy)+(features[index].x+features[index].width))*bins+channel];
-        int three = ptr[((features[index].y+features[index].height)*(size.height+dy)+features[index].x)*bins+channel];
-
-        return four + one - (two + three);
-    }
-
-    Mat evaluate(const Mat &image, const QList<int> &indices) const
-    {
-        int size = indices.empty() ? numFeatures() : indices.size();
-
-        Mat result(1, size, CV_32FC1);
-        for (int i = 0; i < size; i++)
-            result.at<float>(i) = evaluate(image, indices.empty() ? i : indices[i]);
-
-        return result;
-    }
-
-    int numFeatures() const
-    {
-        return features.size()*bins;
-    }
-
-    int numChannels() const
-    {
-        return bins;
-    }
-
-    Size windowSize(int *dx, int *dy) const
-    {
-        if (dx && dy)
-            *dx = *dy = 1;
-        return Size(winWidth, winHeight);
-    }
-
-    int maxCatCount() const { return 0; }
-
-    QList<Rect> features;
-};
-
-BR_REGISTER(Representation, GradientHistogramRepresentation)
-
-} // namespace br
-
-#include "representation/gradienthistogram.moc"
-
-