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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 ...
The Lambda2 method, or Lambda2 vortex criterion, is a vortex core line detection algorithm that can adequately identify vortices from a three-dimensional fluid velocity field. [1] The Lambda2 method is Galilean invariant , which means it produces the same results when a uniform velocity field is added to the existing velocity field or when the ...
Relatively simple to implement and understand, the two-pass algorithm, [13] (also known as the Hoshen–Kopelman algorithm) iterates through 2-dimensional binary data. The algorithm makes two passes over the image: the first pass to assign temporary labels and record equivalences, and the second pass to replace each temporary label by the ...
The Canny algorithm contains a number of adjustable parameters, which can affect the computation time and effectiveness of the algorithm. The size of the Gaussian filter: the smoothing filter used in the first stage directly affects the results of the Canny algorithm. Smaller filters cause less blurring, and allow detection of small, sharp lines.
In contrast to the classic SIFT approach, Wagner et al. use the FAST corner detector for feature detection. The algorithm also distinguishes between the off-line preparation phase where features are created at different scale levels and the on-line phase where features are only created at the current fixed scale level of the phone's camera image.
Hidden-surface algorithms can be used for hidden-line removal, but not the other way around. Reif and Sen [ 17 ] proposed an O (log 4 n )-time algorithm for the hidden-surface problem, using O (( n + v )/log n ) CREW PRAM processors for a restricted model of polyhedral terrains, where v is the output size.
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
"The Bresenham Line-Drawing Algorithm", by Colin Flanagan; Abrash, Michael (1997). Michael Abrash's graphics programming black book. Albany, NY: Coriolis. pp. 654–678. ISBN 978-1-57610-174-2. A very optimized version of the algorithm in C and assembly for use in video games with complete details of its inner workings; Zingl, Alois (2016) [2012].