/// <summary>
/// Computes the filter using the specified <see cref="IntegralImage">
/// Integral Image.</see>
/// </summary>
///
/// <param name="integral">The integral image.</param>
///
public void Compute(IntegralImage integral)
{
for (int i = 0; i < responses.Length; ++i)
{
responses[i].Compute(integral);
}
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
///
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
///
public object Clone()
{
var clone = new IntegralImage(width, height);
integralImage.CopyTo(clone.integralImage, 0);
return(clone);
}
/// <summary>
/// Releases unmanaged and - optionally - managed resources.
/// </summary>
///
/// <param name="disposing"><c>true</c> to release both managed and unmanaged
/// resources; <c>false</c> to release only unmanaged resources.</param>
///
protected virtual void Dispose(bool disposing)
{
if (disposing)
{
// free managed resources
}
this.responses = null;
this.integral = null;
this.descriptor = null;
}
/// <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>
/// Process image looking for interest points.
/// </summary>
///
/// <param name="image">Source image data to process.</param>
///
/// <returns>Returns list of found interest points.</returns>
///
public List <FastRetinaKeypoint> 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);
var features = new List <FastRetinaKeypoint>();
for (int i = 0; i < corners.Count; i++)
{
features.Add(new FastRetinaKeypoint(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 != FastRetinaKeypointDescriptorType.None)
{
descriptor = GetDescriptor();
descriptor.Compute(features);
}
return(features);
}
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);
}
/// <summary>
/// Construct integral image from source grayscale image.
/// </summary>
///
/// <param name="image">Source unmanaged image.</param>
///
/// <returns>Returns integral image.</returns>
///
/// <exception cref="UnsupportedImageFormatException">The source image has incorrect pixel format.</exception>
///
public static IntegralImage FromBitmap(UnmanagedImage image)
{
// check image format
if (image.PixelFormat != PixelFormat.Format8bppIndexed)
{
throw new ArgumentException("Source image can be grayscale (8 bpp indexed) image only.");
}
// get source image size
int width = image.Width;
int height = image.Height;
int offset = image.Stride - width;
// create integral image
var im = new IntegralImage(width, height);
uint[][] matrix = im.matrix;
// do the job
unsafe
{
byte *src = (byte *)image.ImageData.ToPointer();
// for each line
for (int y = 1; y <= height; y++)
{
uint rowSum = 0;
// for each pixel
for (int x = 1; x <= width; x++, src++)
{
image.CheckBounds(src);
rowSum += *src;
matrix[y][x] = rowSum + matrix[y - 1][x];
}
src += offset;
}
}
return(im);
}
/// <summary>
/// Construct integral image from source grayscale image.
/// </summary>
///
/// <param name="image">Source grayscale image.</param>
///
/// <returns>Returns integral image.</returns>
///
/// <exception cref="UnsupportedImageFormatException">The source image has incorrect pixel format.</exception>
///
public static IntegralImage FromBitmap(Bitmap image)
{
// check image format
if (image.PixelFormat != PixelFormat.Format8bppIndexed)
{
throw new UnsupportedImageFormatException("Source image can be grayscale (8 bpp indexed) image only.");
}
// lock source image
BitmapData imageData = image.LockBits(ImageLockMode.ReadOnly);
// process the image
IntegralImage im = FromBitmap(imageData);
// unlock image
image.UnlockBits(imageData);
return(im);
}
/// <summary>
/// Computes the filter for the specified integral image.
/// </summary>
///
/// <param name="image">The integral image.</param>
///
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 = sum(image, i - c + 1, j - b, 2 * c - 1, w)
- sum(image, i - c + 1, j - c / 2, 2 * c - 1, c) * 3;
Dyy = sum(image, i - b, j - c + 1, w, 2 * c - 1)
- sum(image, i - c / 2, j - c + 1, c, 2 * c - 1) * 3;
Dxy = sum(image, i - c, j + 1, c, c)
+ sum(image, i + 1, j - c, c, c)
- sum(image, i - c, j - c, c, c)
- sum(image, i + 1, j + 1, c, c);
// Normalize the filter responses with respect to their size
Dxx *= inv;
Dyy *= inv;
Dxy *= inv;
// 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;
}
}
}
/// <summary>
/// Computes the filter for the specified integral image.
/// </summary>
///
/// <param name="image">The integral image.</param>
///
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;
}
}
}
/// <summary>
/// This method should be implemented by inheriting classes to implement the
/// actual feature extraction, transforming the input image into a list of features.
/// </summary>
///
protected override IEnumerable <FastRetinaKeypoint> InnerTransform(UnmanagedImage 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);
var features = new List <FastRetinaKeypoint>();
for (int i = 0; i < corners.Count; i++)
{
features.Add(new FastRetinaKeypoint(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 != FastRetinaKeypointDescriptorType.None)
{
descriptor = GetDescriptor();
descriptor.Compute(features);
}
return(features);
}
/// <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;
}
private static float sum(IntegralImage img, int row, int col, int rows, int cols)
{
return(img.GetRectangleSum(col, row, col + cols - 1, row + rows - 1) / 255f);
}
/// <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>
/// Process image looking for interest points.
/// </summary>
///
/// <param name="image">Source image data to process.</param>
///
/// <returns>Returns list of found interest points.</returns>
///
/// <exception cref="UnsupportedImageFormatException">
/// The source image has incorrect pixel format.
/// </exception>
///
public List <SurfPoint> 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
UnmanagedImage grayImage = null;
if (image.PixelFormat == PixelFormat.Format8bppIndexed)
{
grayImage = image;
}
else
{
// create temporary grayscale image
grayImage = Grayscale.CommonAlgorithms.BT709.Apply(image);
}
// 1. Compute the integral for the given image
integral = IntegralImage.FromBitmap(grayImage);
// 2. Compute interest point response map
if (responses == null ||
image.Width != responses.Width || image.Height != responses.Height)
{
responses = new ResponseFilters(image.Width, image.Height, octaves, initial);
}
responses.Compute(integral);
// 3. Suppress non-maximum points
List <SurfPoint> featureList = new List <SurfPoint>();
// for each image pyramid in the response map
foreach (ResponseLayer[] layers in responses)
{
// Grab the three layers forming the pyramid
ResponseLayer bot = layers[0]; // bottom layer
ResponseLayer mid = layers[1]; // middle layer
ResponseLayer top = layers[2]; // top layer
int border = (top.Size + 1) / (2 * top.Step);
int tstep = top.Step;
int mstep = mid.Size - bot.Size;
int mscale = mid.Width / top.Width;
int bscale = bot.Width / top.Width;
int r = 1;
// for each row
for (int y = border + 1; y < top.Height - border; y++)
{
// for each pixel
for (int x = border + 1; x < top.Width - border; x++)
{
float currentValue = mid.Responses[y * mscale, x *mscale];
// for each windows' row
for (int i = -r; (currentValue >= threshold) && (i <= r); i++)
{
// for each windows' pixel
for (int j = -r; j <= r; j++)
{
int yi = y + i;
int xj = x + j;
// for each response layer
if (top.Responses[yi, xj] >= currentValue ||
bot.Responses[yi * bscale, xj *bscale] >= currentValue || ((i != 0 || j != 0) &&
mid.Responses[yi * mscale, xj *mscale] >= currentValue))
{
currentValue = 0;
break;
}
}
}
// check if this point is really interesting
if (currentValue >= threshold)
{
// interpolate to sub-pixel precision
double[] offset = interpolate(y, x, top, mid, bot);
if (System.Math.Abs(offset[0]) < 0.5 &&
System.Math.Abs(offset[1]) < 0.5 &&
System.Math.Abs(offset[2]) < 0.5)
{
featureList.Add(new SurfPoint(
(float)((x + offset[0]) * tstep),
(float)((y + offset[1]) * tstep),
(float)(0.1333f * (mid.Size + offset[2] * mstep)),
mid.Laplacian[y * mscale, x * mscale]));
}
}
}
}
}
return(featureList);
}
/// <summary>
/// Construct integral image from source grayscale image.
/// </summary>
///
/// <param name="image">Source unmanaged image.</param>
///
/// <returns>Returns integral image.</returns>
///
/// <exception cref="UnsupportedImageFormatException">The source image has incorrect pixel format.</exception>
///
public static IntegralImage FromBitmap(UnmanagedImage image)
{
// check image format
if (image.PixelFormat != PixelFormat.Format8bppIndexed)
{
throw new ArgumentException("Source image can be graysclae (8 bpp indexed) image only.");
}
// get source image size
int width = image.Width;
int height = image.Height;
int offset = image.Stride - width;
// create integral image
var im = new IntegralImage(width, height);
uint[,] integralImage = im.integralImage;
// do the job
unsafe
{
byte* src = (byte*)image.ImageData.ToPointer();
// for each line
for (int y = 1; y <= height; y++)
{
uint rowSum = 0;
// for each pixel
for (int x = 1; x <= width; x++, src++)
{
rowSum += *src;
integralImage[y, x] = rowSum + integralImage[y - 1, x];
}
src += offset;
}
}
return im;
}
/// <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;
}
private List <SpeededUpRobustFeaturePoint> processImage(UnmanagedImage image)
{
// make sure we have grayscale image
UnmanagedImage grayImage = null;
if (image.PixelFormat == PixelFormat.Format8bppIndexed)
{
grayImage = image;
}
else
{
// create temporary grayscale image
grayImage = Grayscale.CommonAlgorithms.BT709.Apply(image);
}
// 1. Compute the integral for the given image
integral = IntegralImage.FromBitmap(grayImage);
// 2. Create and compute interest point response map
if (responses == null)
{
// re-create only if really needed
responses = new ResponseLayerCollection(image.Width, image.Height, octaves, initial);
}
else
{
responses.Update(image.Width, image.Height, initial);
}
// Compute the response map
responses.Compute(integral);
// 3. Suppress non-maximum points
List <SpeededUpRobustFeaturePoint> featureList =
new List <SpeededUpRobustFeaturePoint>();
// for each image pyramid in the response map
foreach (ResponseLayer[] layers in responses)
{
// Grab the three layers forming the pyramid
ResponseLayer bot = layers[0]; // bottom layer
ResponseLayer mid = layers[1]; // middle layer
ResponseLayer top = layers[2]; // top layer
int border = (top.Size + 1) / (2 * top.Step);
int tstep = top.Step;
int mstep = mid.Size - bot.Size;
int r = 1;
// for each row
for (int y = border + 1; y < top.Height - border; y++)
{
// for each pixel
for (int x = border + 1; x < top.Width - border; x++)
{
int mscale = mid.Width / top.Width;
int bscale = bot.Width / top.Width;
double currentValue = mid.Responses[y * mscale, x *mscale];
// for each windows' row
for (int i = -r; (currentValue >= threshold) && (i <= r); i++)
{
// for each windows' pixel
for (int j = -r; j <= r; j++)
{
int yi = y + i;
int xj = x + j;
// for each response layer
if (top.Responses[yi, xj] >= currentValue ||
bot.Responses[yi * bscale, xj *bscale] >= currentValue || ((i != 0 || j != 0) &&
mid.Responses[yi * mscale, xj *mscale] >= currentValue))
{
currentValue = 0;
break;
}
}
}
// check if this point is really interesting
if (currentValue >= threshold)
{
// interpolate to sub-pixel precision
double[] offset = interpolate(y, x, top, mid, bot);
if (System.Math.Abs(offset[0]) < 0.5 &&
System.Math.Abs(offset[1]) < 0.5 &&
System.Math.Abs(offset[2]) < 0.5)
{
featureList.Add(new SpeededUpRobustFeaturePoint(
(x + offset[0]) * tstep,
(y + offset[1]) * tstep,
0.133333333 * (mid.Size + offset[2] * mstep),
mid.Laplacian[y * mscale, x * mscale]));
}
}
}
}
}
descriptor = null;
if (featureType != SpeededUpRobustFeatureDescriptorType.None)
{
descriptor = new SpeededUpRobustFeaturesDescriptor(integral);
descriptor.Extended = featureType == SpeededUpRobustFeatureDescriptorType.Extended;
descriptor.Invariant = computeOrientation;
descriptor.Compute(featureList);
}
else if (computeOrientation)
{
descriptor = new SpeededUpRobustFeaturesDescriptor(integral);
foreach (var p in featureList)
{
p.Orientation = descriptor.GetOrientation(p);
}
}
return(featureList);
}
/// <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>
/// Creates a new object that is a copy of the current instance.
/// </summary>
///
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
///
public object Clone()
{
var clone = new IntegralImage(width, height);
integralImage.CopyTo(clone.integralImage, 0);
return clone;
}