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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 ...
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 minimum required resolution according to Johnson's criteria are expressed in terms of line pairs of image resolution across a target, in terms of several tasks: [3] Detection, an object is present (1.0 +/− 0.25 line pairs) Orientation, symmetrical, asymmetric, horizontal, or vertical (1.4 +/− 0.35 line pairs)
VLFeat, an open source computer vision library in C (with bindings to multiple languages including MATLAB) has an implementation. LBPLibrary is a collection of eleven Local Binary Patterns (LBP) algorithms developed for background subtraction problem.
Download as PDF; Printable version; In other projects Wikimedia Commons; ... Pages in category "Line codes" The following 46 pages are in this category, out of 46 total.
Foreground detection is one of the major tasks in the field of computer vision and image processing whose aim is to detect changes in image sequences. Background subtraction is any technique which allows an image's foreground to be extracted for further processing (object recognition etc.).
Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [2] navigation of mobile robots, [3] or edge detection in images.