Search results
Results from the WOW.Com Content Network
The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix .
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]).
The scale-invariant feature operator (SFOP) is based on two theoretical concepts: spiral model [2]; feature operator [3]; Desired properties of keypoint detectors:
The algorithm selects one point p randomly and uniformly from P, and recursively finds the minimal circle containing P – {p}, i.e. all of the other points in P except p. If the returned circle also encloses p, it is the minimal circle for the whole of P and is returned. Otherwise, point p must lie on the boundary of the result circle.
The Hough transform [3] can be used to detect lines and the output is a parametric description of the lines in an image, for example ρ = r cos(θ) + c sin(θ). [1] If there is a line in a row and column based image space, it can be defined ρ, the distance from the origin to the line along a perpendicular to the line, and θ, the angle of the perpendicular projection from the origin to the ...
For scale space extrema detection in the SIFT algorithm, the image is first convolved with Gaussian-blurs at different scales. The convolved images are grouped by octave (an octave corresponds to doubling the value of σ {\displaystyle \sigma } ), and the value of k i {\displaystyle k_{i}} is selected so that we obtain a fixed number of ...
Collision detection is the computational problem of detecting an intersection of two or more objects in virtual space. More precisely, it deals with the questions of if , when and where two or more objects intersect.
A recent algorithm for solving the problem as well as a solution classification for it is given in the 2003 IEEE Transactions on Pattern Analysis and Machine Intelligence paper by Gao, et al. [6] An open source implementation of Gao's P3P solver can be found in OpenCV's calib3d module in the solvePnP function. [7]