Class OrientationHistogramSift<Deriv extends ImageGray<Deriv>>
Computes the orientation of a region around a point in scale-space as specified in the SIFT  paper. A histogram of angles is computed using a weighted sum of image derivatives. The size of the region is specified by the scale function parameter. Every pixel inside the sample region is read and contributes to the angle estimation. If the image border is encountered the sample return is truncated.
To get the orientation for the largest peak invoke
- The angle in each bin is set to the atan2(y,x) of the weighted sum of image derivative
- Interpolation is done using a 2nd degree polynomial instead of a parabola.
 Lowe, D. "Distinctive image features from scale-invariant keypoints". International Journal of Computer Vision, 60, 2 (2004), pp.91--110.
Modifier and Type Method Description
()A list of found orientations
()Orientation of the largest peak
(double c_x, double c_y, double sigma)Estimates the orientation(s) of a region at the specified location and scale
Deriv derivX, Deriv derivY)(Specify the input image
OrientationHistogramSiftConfigures orientation estimation
histogramSize- Number of elements in the histogram. Standard is 36
sigmaEnlarge- How much the scale is enlarged by. Standard is 1.5
setImageGradientSpecify the input image
processpublic void process(double c_x, double c_y, double sigma)Estimates the orientation(s) of a region at the specified location and scale
c_x- Location x-axis
c_y- Location y-axis
sigma- blur standard deviations of detected feature. Also referred to as scale.
getOrientationspublic DogArray_F64 getOrientations()A list of found orientations
getPeakOrientationpublic double getPeakOrientation()Orientation of the largest peak