public float Compute(ImageDataPoint <float> point)
{
if (point.ImageID != _currentID)
{
_currentID = point.ImageID;
if (point.Image.IsIntegral || DecisionTree <ImageDataPoint <float>, float[]> .IsBuilding)
{
_integralImage = new FloatArrayHandler(point.Image.RawArray, true);
}
else
{
_integralImage = IntegralImage.ComputeFloat <FloatArrayHandler>(point.Image);
}
}
int row = point.Row;
int column = point.Column;
IMultichannelImage <float> image = point.Image;
float sum = 0;
for (int i = 0; i < _count; i++)
{
if (i % 2 == 0)
{
sum += _integralImage.ComputeRectangleSum(row, column, _channels[i], _rectangles[i]);
}
else
{
sum -= _integralImage.ComputeRectangleSum(row, column, _channels[i], _rectangles[i]);
}
}
Debug.Assert(!float.IsNaN(sum), "Rectangle sum is NaN!");
return(sum);
}
public override object Task2()
{
IntegralImage ii = new IntegralImage(powerGrid);
(int, int, int)gridBox = (0, 0, 0);
int bestBoxValue = int.MinValue;
for (int size = 1; size < gridSize; size++)
{
for (int y = 0; y < gridSize - size; y++)
{
for (int x = 0; x < gridSize - size; x++)
{
int v = ii.AreaSum(x, y, size, size);
if (v > bestBoxValue)
{
bestBoxValue = v;
gridBox = (x - size + 1, y - size + 1, size);
}
}
}
}
System.Console.WriteLine(bestBoxValue);
return($"{gridBox.Item1},{gridBox.Item2},{gridBox.Item3}");
}
public void Compute(IntegralImage integral)
{
for (int i = 0; i < responses.Length; ++i)
{
responses[i].Compute(integral);
}
}
public void build_integral_image()
{
System.Drawing.Bitmap img = new System.Drawing.Bitmap(path);
iimg = IntegralImage.FromImage(img);
img.Dispose();
integral_image = true;
}
/// <summary>Process the filter on the specified image.</summary>
/// <param name="image">Source image data.</param>
protected override unsafe void ProcessFilter(UnmanagedImage image)
{
IntegralImage im = IntegralImage.FromBitmap(image);
int width = image.Width;
int height = image.Height;
int widthM1 = width - 1;
int heightM1 = height - 1;
int offset = image.Stride - width;
int radius = windowSize / 2;
float avgBrightnessPart = 1.0f - pixelBrightnessDifferenceLimit;
byte * ptr = (byte *)image.ImageData.ToPointer( );
for (int y = 0; y < height; y++)
{
int y1 = (y - radius < 0) ? 0 : y - radius;
int y2 = (y + radius > heightM1) ? heightM1 : y + radius;
for (int x = 0; x < width; x++, ptr++)
{
int x1 = (x - radius < 0) ? 0 : x - radius;
int x2 = (x + radius > widthM1) ? widthM1 : x + radius;
float mean = im.GetRectangleMeanUnsafe(x1, y1, x2, y2);
* ptr = (byte)((mean < upperLimit && *ptr < (int)(mean * avgBrightnessPart)) ? 0 : 255);
}
ptr += offset;
}
}
public void TestStaticFilter0()
{
double[] data =
{
1.0, 2.0, 3.0,
4.0, 5.0, 6.0,
7.0, 8.0, 9.0,
};
Image image = new Image(3, data);
IntegralImage integral_image = new IntegralImage(image);
double res;
res = Filter.Filter0(integral_image, 0, 0, 1, 1, Filter.Subtract);
Assert.AreEqual(1.0, res, TestsHelper.EPS);
res = Filter.Filter0(integral_image, 0, 0, 2, 2, Filter.Subtract);
Assert.AreEqual(12.0, res, TestsHelper.EPS);
res = Filter.Filter0(integral_image, 0, 0, 3, 3, Filter.Subtract);
Assert.AreEqual(45.0, res, TestsHelper.EPS);
res = Filter.Filter0(integral_image, 1, 1, 2, 2, Filter.Subtract);
Assert.AreEqual(28.0, res, TestsHelper.EPS);
res = Filter.Filter0(integral_image, 2, 2, 1, 1, Filter.Subtract);
Assert.AreEqual(9.0, res, TestsHelper.EPS);
res = Filter.Filter0(integral_image, 0, 0, 3, 1, Filter.Subtract);
Assert.AreEqual(12.0, res, TestsHelper.EPS);
res = Filter.Filter0(integral_image, 0, 0, 1, 3, Filter.Subtract);
Assert.AreEqual(6.0, res, TestsHelper.EPS);
}
public void FromImageTest()
{
foreach (int bitsPerPixel in new[] { 8 /*, 16*/ })
{
Image src = new Image(23, 20, bitsPerPixel, 200, 200);
src.Randomize(this.random);
IntegralImage dst = IntegralImage.FromImage(src);
Assert.AreEqual(src.Width + 1, dst.Width);
Assert.AreEqual(src.Height + 1, dst.Height);
for (int x = 0; x < src.Width; x++)
{
for (int y = 0; y < src.Height; y++)
{
int actual = dst[x + 1, y + 1];
int expected = 0;
for (int ix = 0; ix <= x; ix++)
{
for (int iy = 0; iy <= y; iy++)
{
expected += (int)src.GetPixel(ix, iy);
}
}
Assert.AreEqual(expected, actual);
}
}
}
}
static void Main(string[] args)
{
int name = 0;
while (File.Exists($"img{name}.bmp"))
{
Image img = new Image(new Bitmap($"img{name}.bmp"));
IntegralImage integral = new IntegralImage(img);
}
}
/// <summary>
/// Process the filter on the specified image.
/// </summary>
///
/// <param name="image">Source image data.</param>
///
protected override unsafe void ProcessFilter(UnmanagedImage image)
{
// create integral image
IntegralImage im = IntegralImage.FromBitmap(image);
int width = image.Width;
int height = image.Height;
int widthM1 = width - 1;
int heightM1 = height - 1;
int offset = image.Stride - width;
int radius = windowSize / 2;
float avgBrightnessPart = 1.0f - pixelBrightnessDifferenceLimit;
byte *ptr = (byte *)image.ImageData.ToPointer( );
for (int y = 0; y < height; y++)
{
// rectangle's Y coordinates
int y1 = y - radius;
int y2 = y + radius;
if (y1 < 0)
{
y1 = 0;
}
if (y2 > heightM1)
{
y2 = heightM1;
}
for (int x = 0; x < width; x++, ptr++)
{
// rectangle's X coordinates
int x1 = x - radius;
int x2 = x + radius;
if (x1 < 0)
{
x1 = 0;
}
if (x2 > widthM1)
{
x2 = widthM1;
}
// *ptr = (byte) ( ( *ptr < (int) ( im.GetRectangleMeanUnsafe( x1, y1, x2, y2 ) * avgBrightnessPart ) ) ? 0 : 255 );
//*ptr = (byte) ( im.GetRectangleMeanUnsafe( x1, y1, x2, y2 ) * 255);
ptr[RGB.R] = ptr[RGB.R] = ptr[RGB.R] = (byte)(im.GetRectangleMeanUnsafe(x1, y1, x2, y2));
}
ptr += offset;
}
}
/// <summary>
/// Initializes a new instance of the <see cref="ScaleInvariantFeatureTranformKeypointDescriptor"/> class.
/// </summary>
///
internal ScaleInvariantFeatureTranformKeypointDescriptor(UnmanagedImage image,
IntegralImage integral, ScaleInvariantFeatureTranformKeypointPattern pattern)
{
this.Extended = false;
this.IsOrientationNormal = true;
this.IsScaleNormal = true;
this.Image = image;
this.Integral = integral;
this._pattern = pattern;
}
/// <summary>
/// Process the filter on the specified image.
/// </summary>
///
/// <param name="image">Source image data.</param>
///
protected override unsafe void ProcessFilter(UnmanagedImage image)
{
// create integral image
var im = IntegralImage.FromBitmap(image);
var width = image.Width;
var height = image.Height;
var widthM1 = width - 1;
var heightM1 = height - 1;
var offset = image.Stride - width;
var radius = this.windowSize / 2;
var avgBrightnessPart = 1.0f - this.pixelBrightnessDifferenceLimit;
var ptr = (byte *)image.ImageData.ToPointer( );
for (var y = 0; y < height; y++)
{
// rectangle's Y coordinates
var y1 = y - radius;
var y2 = y + radius;
if (y1 < 0)
{
y1 = 0;
}
if (y2 > heightM1)
{
y2 = heightM1;
}
for (var x = 0; x < width; x++, ptr++)
{
// rectangle's X coordinates
var x1 = x - radius;
var x2 = x + radius;
if (x1 < 0)
{
x1 = 0;
}
if (x2 > widthM1)
{
x2 = widthM1;
}
*ptr = (byte)((*ptr < (int)(im.GetRectangleMeanUnsafe(x1, y1, x2, y2) * avgBrightnessPart)) ? 0 : 255);
}
ptr += offset;
}
}
public void TestVertical1D()
{
double[] data =
{
1.0, 2.0, 3.0
};
Image image = new Image(1, data);
IntegralImage integral_image = new IntegralImage(image);
Assert.AreEqual(1.0, integral_image[0][0]);
Assert.AreEqual(3.0, integral_image[1][0]);
Assert.AreEqual(6.0, integral_image[2][0]);
}
public void TestHorizontal1D()
{
double[] data =
{
1.0, 2.0, 3.0
};
Image image = new Image(3, data);
IntegralImage integral_image = new IntegralImage(image);
Assert.AreEqual(1.0, integral_image[0][0]);
Assert.AreEqual(3.0, integral_image[0][1]);
Assert.AreEqual(6.0, integral_image[0][2]);
}
public IntegralImageTest()
{
UnmanagedImage uImage = UnmanagedImage.Create(10, 10, PixelFormat.Format8bppIndexed);
for (int y = 0; y < 10; y++)
{
for (int x = 0; x < 10; x++)
{
uImage.SetPixel(x, y, ((x + y) % 2 == 0) ? Color.FromArgb(0, 0, 0) : Color.FromArgb(1, 1, 1));
}
}
integralImage = IntegralImage.FromBitmap(uImage);
}
public void TestStaticFilter5()
{
double[] data =
{
1.0, 2.0, 3.0,
3.0, 4.0, 5.0,
6.0, 7.0, 8.0,
};
Image image = new Image(3, data);
IntegralImage integral_image = new IntegralImage(image);
double res = Filter.Filter5(integral_image, 0, 0, 3, 3, Filter.Subtract);
Assert.AreEqual(-15.0, res, TestsHelper.EPS); // 3+4+5 - (1+2+3) - (6+7+8)
}
public List <ScaleInvariantFeatureTranformKeypoint> ProcessImage(UnmanagedImage image)
{
// check image format
if (
(image.PixelFormat != PixelFormat.Format8bppIndexed) &&
(image.PixelFormat != PixelFormat.Format24bppRgb) &&
(image.PixelFormat != PixelFormat.Format32bppRgb) &&
(image.PixelFormat != PixelFormat.Format32bppArgb)
)
{
throw new UnsupportedImageFormatException("Unsupported pixel format of the source image.");
}
// make sure we have grayscale image
if (image.PixelFormat == PixelFormat.Format8bppIndexed)
{
_grayImage = image;
}
else
{
// create temporary grayscale image
_grayImage = Grayscale.CommonAlgorithms.BT709.Apply(image);
}
// 1. Extract corners points from the image.
List <IntPoint> corners = Detector.ProcessImage(_grayImage);
List <ScaleInvariantFeatureTranformKeypoint> features = new List <ScaleInvariantFeatureTranformKeypoint>();
for (int i = 0; i < corners.Count; i++)
{
features.Add(new ScaleInvariantFeatureTranformKeypoint(corners[i].X, corners[i].Y));
}
// 2. Compute the integral for the given image
_integral = IntegralImage.FromBitmap(_grayImage);
// 3. Compute feature descriptors if required
_descriptor = null;
if (_featureType != ScaleInvariantFeatureTranformKeypointDescriptorType.None)
{
_descriptor = GetDescriptor();
_descriptor.Compute(features);
}
return(features);
}
public void TestFilter0()
{
Image image = new Image(2, 2);
image.Set(0, 0, 0.0);
image.Set(0, 1, 1.0);
image.Set(1, 0, 2.0);
image.Set(1, 1, 3.0);
Filter flt1 = new Filter(0, 0, 1, 1);
IntegralImage integral_image = new IntegralImage(image);
Assert.AreEqual(0.0, flt1.Apply(integral_image, 0), TestsHelper.EPS);
Assert.AreEqual(1.0986123, flt1.Apply(integral_image, 1), TestsHelper.EPS);
}
public void TestBasic2D()
{
double[] data =
{
1.0, 2.0,
3.0, 4.0,
};
Image image = new Image(2, data);
IntegralImage integral_image = new IntegralImage(image);
Assert.AreEqual(1.0, integral_image[0][0]);
Assert.AreEqual(3.0, integral_image[0][1]);
Assert.AreEqual(4.0, integral_image[1][0]);
Assert.AreEqual(10.0, integral_image[1][1]);
}
public void DescribeInterestPoints(List<InterestingPoint> ipts, bool upright, bool extended, IntegralImage img)
{
if (ipts.Count == 0) return;
this.img = img;
foreach (InterestingPoint ip in ipts)
{
// determine descriptor size
if (extended) ip.DescriptorLength = 128;
else ip.DescriptorLength = 64;
// if we want rotation invariance get the orientation
if (!upright) GetOrientation(ip);
// Extract SURF descriptor
GetDescriptor(ip, upright, extended);
}
}
protected override unsafe void ProcessFilter(UnmanagedImage image)
{
IntegralImage image2 = IntegralImage.FromBitmap(image);
int width = image.Width;
int height = image.Height;
int num3 = width - 1;
int num4 = height - 1;
int num5 = image.Stride - width;
int num6 = this.windowSize / 2;
float num7 = 1f - this.pixelBrightnessDifferenceLimit;
byte * numPtr = (byte *)image.ImageData.ToPointer();
for (int i = 0; i < height; i++)
{
int num9 = i - num6;
int num10 = i + num6;
if (num9 < 0)
{
num9 = 0;
}
if (num10 > num4)
{
num10 = num4;
}
int num11 = 0;
while (num11 < width)
{
int num12 = num11 - num6;
int num13 = num11 + num6;
if (num12 < 0)
{
num12 = 0;
}
if (num13 > num3)
{
num13 = num3;
}
numPtr[0] = (numPtr[0] < ((int)(image2.GetRectangleMeanUnsafe(num12, num9, num13, num10) * num7))) ? ((byte)0) : ((byte)0xff);
num11++;
numPtr++;
}
numPtr += num5;
}
}
protected unsafe override void ProcessFilter(UnmanagedImage image)
{
IntegralImage integralImage = IntegralImage.FromBitmap(image);
int width = image.Width;
int height = image.Height;
int num = width - 1;
int num2 = height - 1;
int num3 = image.Stride - width;
int num4 = windowSize / 2;
float num5 = 1f - pixelBrightnessDifferenceLimit;
byte * ptr = (byte *)image.ImageData.ToPointer();
for (int i = 0; i < height; i++)
{
int num6 = i - num4;
int num7 = i + num4;
if (num6 < 0)
{
num6 = 0;
}
if (num7 > num2)
{
num7 = num2;
}
int num8 = 0;
while (num8 < width)
{
int num9 = num8 - num4;
int num10 = num8 + num4;
if (num9 < 0)
{
num9 = 0;
}
if (num10 > num)
{
num10 = num;
}
*ptr = (byte)((*ptr >= (int)(integralImage.GetRectangleMeanUnsafe(num9, num6, num10, num7) * num5)) ? 255 : 0);
num8++;
ptr++;
}
ptr += num3;
}
}
/// <summary>
/// Process the filter on the specified image.
///
/// </summary>
/// <param name="image">Source image data.</param>
protected override unsafe void ProcessFilter(UnmanagedImage image)
{
IntegralImage integralImage = IntegralImage.FromBitmap(image);
int width = image.Width;
int height = image.Height;
int num1 = width - 1;
int num2 = height - 1;
int num3 = image.Stride - width;
int num4 = _windowSize / 2;
float num5 = 1f - _pixelBrightnessDifferenceLimit;
byte * numPtr = (byte *)image.ImageData.ToPointer();
for (int index = 0; index < height; ++index)
{
int y1 = index - num4;
int y2 = index + num4;
if (y1 < 0)
{
y1 = 0;
}
if (y2 > num2)
{
y2 = num2;
}
int num6 = 0;
while (num6 < width)
{
int x1 = num6 - num4;
int x2 = num6 + num4;
if (x1 < 0)
{
x1 = 0;
}
if (x2 > num1)
{
x2 = num1;
}
*numPtr = (int)*numPtr < (int)((double)integralImage.GetRectangleMeanUnsafe(x1, y1, x2, y2) * (double)num5) ? (byte)0 : byte.MaxValue;
++num6;
++numPtr;
}
numPtr += num3;
}
}
public void TestStaticFilter2()
{
double[] data =
{
1.0, 2.0, 3.0,
3.0, 4.0, 5.0,
6.0, 7.0, 8.0,
};
Image image = new Image(3, data);
IntegralImage integral_image = new IntegralImage(image);
double res;
res = Filter.Filter2(integral_image, 0, 0, 2, 1, Filter.Subtract);
Assert.AreEqual(2.0, res, TestsHelper.EPS); // 3 - 1
res = Filter.Filter2(integral_image, 0, 0, 2, 2, Filter.Subtract);
Assert.AreEqual(4.0, res, TestsHelper.EPS); // 3+4 - 1+2
res = Filter.Filter2(integral_image, 0, 0, 2, 3, Filter.Subtract);
Assert.AreEqual(6.0, res, TestsHelper.EPS); // 3+4+5 - 1+2+3
}
public void TestStaticFilter3()
{
double[] data =
{
1.0, 2.1, 3.4,
3.1, 4.1, 5.1,
6.0, 7.1, 8.0,
};
Image image = new Image(3, data);
IntegralImage integral_image = new IntegralImage(image);
double res;
res = Filter.Filter3(integral_image, 0, 0, 2, 2, Filter.Subtract);
Assert.AreEqual(0.1, res, TestsHelper.EPS); // 2.1+3.1 - 1+4.1
res = Filter.Filter3(integral_image, 1, 1, 2, 2, Filter.Subtract);
Assert.AreEqual(0.1, res, TestsHelper.EPS); // 4+8 - 5+7
res = Filter.Filter3(integral_image, 0, 1, 2, 2, Filter.Subtract);
Assert.AreEqual(0.3, res, TestsHelper.EPS); // 2.1+5.1 - 3.4+4.1
}
public void TestCalculateSubfingerprint()
{
Image image = new Image(2, 2);
image[0, 0] = 0.0;
image[0, 1] = 1.0;
image[1, 0] = 2.0;
image[1, 1] = 3.0;
Classifier[] classifiers =
{
new Classifier(new Filter(0, 0, 1, 1), new Quantizer(0.01, 1.01, 1.5)),
};
FingerprintCalculator calculator = new FingerprintCalculator(classifiers);
IntegralImage integral_image = new IntegralImage(image);
Assert.AreEqual(TestsHelper.GrayCode(0), calculator.CalculateSubfingerprint(integral_image, 0));
Assert.AreEqual(TestsHelper.GrayCode(2), calculator.CalculateSubfingerprint(integral_image, 1));
}
public float Compute(ImageDataPoint <float> point)
{
if (point.ImageID != _currentID)
{
_currentID = point.ImageID;
if (point.Image.IsIntegral || DecisionTree <ImageDataPoint <float>, float[]> .IsBuilding)
{
_integralImage = point.Image;
}
else
{
_integralImage = IntegralImage.ComputeFloat <FloatArrayHandler>(point.Image);
}
}
int row = point.Row;
int column = point.Column;
float sum = _integralImage.ComputeRectangleSum(row, column, _channel, _rect);
Debug.Assert(!float.IsNaN(sum), "Rectangle sum is NaN");
return(sum);
}
public void Compute(IntegralImage image)
{
int b = (Size - 1) / 2 + 1;
int c = Size / 3;
int w = Size;
float inv = 1f / (w * w);
float Dxx, Dyy, Dxy;
for (int y = 0; y < Height; y++)
{
for (int x = 0; x < Width; x++)
{
// Get the image coordinates
int i = y * Step;
int j = x * Step;
// Compute response components
Dxx = ((int)image.GetRectangleSum(j - b, i - c + 1, j - b + w - 1, i - c + 2 * c - 1)
- (int)image.GetRectangleSum(j - c / 2, i - c + 1, j - c / 2 + c - 1, i - c + 2 * c - 1) * 3);
Dyy = ((int)image.GetRectangleSum(j - c + 1, i - b, j - c + 2 * c - 1, i - b + w - 1)
- (int)image.GetRectangleSum(j - c + 1, i - c / 2, j - c + 2 * c - 1, i - c / 2 + c - 1) * 3);
Dxy = ((int)image.GetRectangleSum(j + 1, i - c, j + c, i - 1)
+ (int)image.GetRectangleSum(j - c, i + 1, j - 1, i + c)
- (int)image.GetRectangleSum(j - c, i - c, j - 1, i - 1)
- (int)image.GetRectangleSum(j + 1, i + 1, j + c, i + c));
// Normalize the filter responses with respect to their size
Dxx *= inv / 255f;
Dyy *= inv / 255f;
Dxy *= inv / 255f;
// Get the determinant of Hessian response & laplacian sign
Responses[y, x] = (Dxx * Dyy) - (0.9f * 0.9f * Dxy * Dxy);
Laplacian[y, x] = (Dxx + Dyy) >= 0 ? 1 : 0;
}
}
}
public void TestStaticFilter1()
{
double[] data =
{
1.0, 2.1, 3.4,
3.1, 4.1, 5.1,
6.0, 7.1, 8.0
};
Image image = new Image(3, data);
IntegralImage integral_image = new IntegralImage(image);
double res;
res = Filter.Filter1(integral_image, 0, 0, 1, 1, Filter.Subtract);
Assert.AreEqual(1.0 - 0.0, res);
res = Filter.Filter1(integral_image, 1, 1, 1, 1, Filter.Subtract);
Assert.AreEqual(4.1 - 0.0, res);
res = Filter.Filter1(integral_image, 0, 0, 1, 2, Filter.Subtract);
Assert.AreEqual(2.1 - 1.0, res);
res = Filter.Filter1(integral_image, 0, 0, 2, 2, Filter.Subtract);
Assert.AreEqual((2.1 + 4.1) - (1.0 + 3.1), res);
res = Filter.Filter1(integral_image, 0, 0, 3, 2, Filter.Subtract);
Assert.AreEqual((2.1 + 4.1 + 7.1) - (1.0 + 3.1 + 6.0), res);
}
private void btnRunSurf_Click(object sender, EventArgs e)
{
OpenFileDialog openFileDialog = new OpenFileDialog();
openFileDialog.ShowDialog();
string pathToFile = openFileDialog.FileName;
Stopwatch watch = new Stopwatch();
watch.Start();
try
{
// Load an Image
Bitmap img = new Bitmap(pathToFile);
pbMainPicture.Image = img;
// Create Integral Image
IntegralImage iimg = IntegralImage.FromImage(img);
// Extract the interest points
ipts = FastHessian.getIpoints(0.0002f, 5, 2, iimg);
// Describe the interest points
SurfDescriptor.DecribeInterestPoints(ipts, false, false, iimg);
// Draw points on the image
PaintSURF(img, ipts);
}
catch
{
}
watch.Stop();
this.Text = "DemoSURF - Elapsed time: " + watch.Elapsed +
" for " + ipts.Count + "points";
}
public void TestArea()
{
double[] data =
{
1.0, 2.0, 3.0,
4.0, 5.0, 6.0,
7.0, 8.0, 9.0,
};
Image image = new Image(3, data);
IntegralImage integral_image = new IntegralImage(image);
Assert.AreEqual((1.0), integral_image.Area(0, 0, 0, 0));
Assert.AreEqual((1.0 + 4.0), integral_image.Area(0, 0, 1, 0));
Assert.AreEqual((1.0 + 4.0 + 7.0), integral_image.Area(0, 0, 2, 0));
Assert.AreEqual((1.0) + (2.0), integral_image.Area(0, 0, 0, 1));
Assert.AreEqual((1.0 + 4.0) + (2.0 + 5.0), integral_image.Area(0, 0, 1, 1));
Assert.AreEqual((1.0 + 4.0 + 7.0) + (2.0 + 5.0 + 8.0), integral_image.Area(0, 0, 2, 1));
Assert.AreEqual((2.0), integral_image.Area(0, 1, 0, 1));
Assert.AreEqual((2.0 + 5.0), integral_image.Area(0, 1, 1, 1));
Assert.AreEqual((2.0 + 5.0 + 8.0), integral_image.Area(0, 1, 2, 1));
}
public SpeededUpRobustFeaturesDescriptor(IntegralImage integralImage)
{
_integral = integralImage;
}
public static void DecribeInterestPoints(List<InterestingPoint> ipts, bool upright, bool extended, IntegralImage img)
{
SurfDescriptor des = new SurfDescriptor();
des.DescribeInterestPoints(ipts, upright, extended, img);
}
public int Classify(IntegralImage image, int offset)
{
double value = m_filter.Apply(image, offset);
return m_quantizer.Quantize(value);
}
/// <summary>
/// Initializes a new instance of the <see cref="FastRetinaKeypointDescriptor"/> class.
/// </summary>
///
internal FastRetinaKeypointDescriptor(UnmanagedImage image,
IntegralImage integral, FastRetinaKeypointPattern pattern)
{
this.Extended = false;
this.IsOrientationNormal = true;
this.IsScaleNormal = true;
this.Image = image;
this.Integral = integral;
this.pattern = pattern;
}
/// <summary>
/// Initializes a new instance of the <see cref="SpeededUpRobustFeaturesDescriptor"/> class.
/// </summary>
///
/// <param name="integralImage">
/// The integral image which is the source of the feature points.
/// </param>
///
public SpeededUpRobustFeaturesDescriptor(IntegralImage integralImage)
{
this.integral = integralImage;
}
/// <summary>
/// Initializes a new instance of the <see cref="SurfDescriptor"/> class.
/// </summary>
///
/// <param name="integralImage">
/// The integral image which is the source of the feature points.
/// </param>
///
public SurfDescriptor(IntegralImage integralImage)
{
this.integral = integralImage;
}