public VisualizeAssociationMatchesApp(Class<T> imageType, Class<D> derivType) {
super(3);
this.imageType = imageType;
GeneralFeatureDetector<T, D> alg;
addAlgorithm(
0,
"Fast Hessian",
FactoryInterestPoint.fastHessian(new ConfigFastHessian(1, 2, 200, 1, 9, 4, 4)));
if (imageType == ImageFloat32.class)
addAlgorithm(
0, "SIFT", FactoryInterestPoint.siftDetector(null, new ConfigSiftDetector(2, 5, 200, 5)));
alg =
FactoryDetectPoint.createShiTomasi(new ConfigGeneralDetector(500, 2, 1), false, derivType);
addAlgorithm(0, "Shi-Tomasi", FactoryInterestPoint.wrapPoint(alg, 1, imageType, derivType));
addAlgorithm(1, "SURF-S", FactoryDescribeRegionPoint.surfStable(null, imageType));
addAlgorithm(
1,
"SURF-S Color",
FactoryDescribeRegionPoint.surfColorStable(null, ImageType.ms(3, imageType)));
if (imageType == ImageFloat32.class)
addAlgorithm(1, "SIFT", FactoryDescribeRegionPoint.sift(null, null));
addAlgorithm(1, "BRIEF", FactoryDescribeRegionPoint.brief(new ConfigBrief(true), imageType));
addAlgorithm(1, "BRIEFSO", FactoryDescribeRegionPoint.brief(new ConfigBrief(false), imageType));
addAlgorithm(1, "Pixel 11x11", FactoryDescribeRegionPoint.pixel(11, 11, imageType));
addAlgorithm(1, "NCC 11x11", FactoryDescribeRegionPoint.pixelNCC(11, 11, imageType));
addAlgorithm(2, "Greedy", false);
addAlgorithm(2, "Backwards", true);
// estimate orientation using this once since it is fast and accurate
Class integralType = GIntegralImageOps.getIntegralType(imageType);
OrientationIntegral orientationII = FactoryOrientationAlgs.sliding_ii(null, integralType);
orientation = FactoryOrientation.convertImage(orientationII, imageType);
imageLeft = new MultiSpectral<T>(imageType, 1, 1, 3);
imageRight = new MultiSpectral<T>(imageType, 1, 1, 3);
grayLeft = GeneralizedImageOps.createSingleBand(imageType, 1, 1);
grayRight = GeneralizedImageOps.createSingleBand(imageType, 1, 1);
setMainGUI(panel);
}
public <II extends ImageSingleBand> double[][] harder(BufferedImage image) {
MultiSpectral<ImageFloat32> colorImage =
ConvertBufferedImage.convertFromMulti(image, null, true, ImageFloat32.class);
// convert the color image to greyscale
ImageFloat32 greyscaleImage =
ConvertImage.average((MultiSpectral<ImageFloat32>) colorImage, null);
// SURF works off of integral images
Class<II> integralType = GIntegralImageOps.getIntegralType(ImageFloat32.class);
// define the feature detection algorithm
NonMaxSuppression extractor =
FactoryFeatureExtractor.nonmax(new ConfigExtract(2, detectThreshold, 5, true));
FastHessianFeatureDetector<II> detector =
new FastHessianFeatureDetector<II>(extractor, maxFeaturesPerScale, 2, 9, 4, 4);
// estimate orientation
OrientationIntegral<II> orientation = FactoryOrientationAlgs.sliding_ii(null, integralType);
DescribePointSurf<II> descriptor =
FactoryDescribePointAlgs.<II>surfStability(null, integralType);
// compute the integral image of the greyscale 'image'
II integralgrey =
GeneralizedImageOps.createSingleBand(
integralType, greyscaleImage.width, greyscaleImage.height);
GIntegralImageOps.transform(greyscaleImage, integralgrey);
// detect fast hessian features
detector.detect(integralgrey);
// === This is the point were the code starts deviating from the standard SURF! ===
// tell algorithms which image to process
orientation.setImage(integralgrey);
List<ScalePoint> points = detector.getFoundPoints();
double[][] descriptions = new double[points.size()][3 * descriptor.getDescriptionLength()];
double[] angles = new double[points.size()];
int l = 0;
for (ScalePoint p : points) {
orientation.setScale(p.scale);
angles[l] = orientation.compute(p.x, p.y);
l++;
}
for (int i = 0; i < 3; i++) {
// check if it is actually a greyscale image, take always the 1st band!
ImageFloat32 colorImageBand = null;
if (colorImage.getNumBands() == 1) {
colorImageBand = colorImage.getBand(0);
} else {
colorImageBand = colorImage.getBand(i);
}
// compute the integral image of the i-th band of the color 'image'
II integralband =
GeneralizedImageOps.createSingleBand(
integralType, colorImageBand.width, colorImageBand.height);
GIntegralImageOps.transform(colorImageBand, integralband);
// tell algorithms which image to process
// orientation.setImage(integralband);
descriptor.setImage(integralband);
int j = 0;
for (ScalePoint p : points) {
// estimate orientation
// orientation.setScale(p.scale);
// double angle = orientation.compute(p.x, p.y);
// extract the SURF description for this region
SurfFeature desc = descriptor.createDescription();
descriptor.describe(p.x, p.y, angles[j], p.scale, (TupleDesc_F64) desc);
double[] banddesc = desc.getValue();
if (perBandNormalization) {
banddesc = Normalization.normalizeL2(banddesc);
}
for (int k = 0; k < SURFLength; k++) {
descriptions[j][i * SURFLength + k] = banddesc[k];
}
j++;
}
}
return descriptions;
}
