public void process(BufferedImage input) {
setInputImage(input);
image.reshape(input.getWidth(), input.getHeight());
transform.reshape(input.getWidth(), input.getHeight());
magnitude.reshape(input.getWidth(), input.getHeight());
phase.reshape(input.getWidth(), input.getHeight());
ConvertBufferedImage.convertFrom(input, image, true);
fft.forward(image, transform);
GDiscreteFourierTransformOps.shiftZeroFrequency(transform, true);
GDiscreteFourierTransformOps.magnitude(transform, magnitude);
GDiscreteFourierTransformOps.phase(transform, phase);
// Convert it to a log scale for visibility
GPixelMath.log(magnitude, magnitude);
SwingUtilities.invokeLater(
new Runnable() {
public void run() {
setPreferredSize(new Dimension(image.width + 50, image.height + 20));
processedImage = true;
}
});
doRefreshAll();
}
public Segmenter(ImageUInt8 gray) {
// Downsample image to smaller size
int sampleWidth = 300;
this.scale = (1.0 * gray.getWidth()) / sampleWidth;
int sampleHeight = (int) (gray.getHeight() / scale);
ImageUInt8 sample = new ImageUInt8(sampleWidth, sampleHeight);
boofcv.alg.distort.DistortImageOps.scale(
gray, sample, boofcv.alg.interpolate.TypeInterpolate.NEAREST_NEIGHBOR);
this.sample = sample;
// Calculate mean
this.mean = GPixelMath.sum(gray) / (gray.width * gray.height);
this.threshold = this.calculateThreshold();
Log.i(
"Setalyzer",
"brightness histogram: " + Arrays.toString(this.brightnessHistogram.histogram));
// Blur image and store blurred image
this.blurred = boofcv.alg.filter.blur.BlurImageOps.mean(sample, null, BLUR_RADIUS, null);
// Create binary image and label blobs for threshold-based segmentation
// Log.i("Setalyzer", "THreshold value is " + this.mean);
// Threshold to generate binary image
ImageUInt8 binary =
boofcv.alg.filter.binary.ThresholdImageOps.threshold(
this.blurred, null, (int) this.mean, false);
ImageSInt32 blobImage =
FactoryImage.create(ImageSInt32.class, sample.getWidth(), sample.getHeight());
this.numBlobs = boofcv.alg.filter.binary.BinaryImageOps.labelBlobs4(binary, blobImage);
this.blobQuads = quadsFromBlobs(blobImage, numBlobs);
// Canny detect edges and store them
// Dynamic canny edge, which sets the threshold as a function of the image's edge intensity
DetectEdgeContour<ImageUInt8> cannyD =
FactoryDetectEdgeContour.canny(0.05, 0.15, true, ImageUInt8.class, ImageSInt16.class);
cannyD.process(blurred);
List<List<Point2D_I32>> edges = cannyD.getContours();
// Prune edges which are obviously not cards
List<List<Point2D_F64>> prunedEdgeList = new ArrayList<List<Point2D_F64>>();
for (List<Point2D_I32> edge : edges) {
// Disregard tiny contours
if (edge.size() < EDGE_SIZE_THRESHOLD) {
continue;
}
// Disregard shapes with blatantly non-card shapes
// if (!isCardShaped(edge)) {
// continue;
// }
List<Point2D_F64> f64Edge = new ArrayList<Point2D_F64>();
for (Point2D_I32 p : edge) {
f64Edge.add(new Point2D_F64(p.x, p.y));
}
prunedEdgeList.add(f64Edge);
}
this.prunedCannyEdgeList = prunedEdgeList;
}