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In image processing, line detection is an algorithm that takes a collection of n edge points and finds all the lines on which these edge points lie. [1] The most popular line detectors are the Hough transform and convolution -based techniques.
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 ...
The Hough transform (/ h ĘŚ f /) is a feature extraction technique used in image analysis, computer vision, pattern recognition, and digital image processing. [1] [2] The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.
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.
Notice that the points (2,1) and (2,3) are on opposite sides of the line and (,) evaluates to positive or negative. A line splits a plane into halves and the half-plane that has a negative (,) can be called the negative half-plane, and the other half can be called the positive half-plane. This observation is very important in the remainder of ...
The grid structure of a chessboard naturally defines two sets of parallel lines in an image of it. Therefore, one expects that line detection algorithms should successfully detect these lines in practice. Indeed, the following figure demonstrates Hough transform-based line detection applied to a perspective-transformed chessboard image. Clearly ...
The first corner detection algorithm based on the AST is FAST (features from accelerated segment test). [29] Although r {\displaystyle r} can in principle take any value, FAST uses only a value of 3 (corresponding to a circle of 16 pixels circumference), and tests show that the best results are achieved with n {\displaystyle n} being 9.
A robust background subtraction algorithm should be able to handle lighting changes, repetitive motions from clutter and long-term scene changes. [2] The following analyses make use of the function of V ( x , y , t ) as a video sequence where t is the time dimension, x and y are the pixel location variables. e.g. V (1,2,3) is the pixel ...