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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.
Edge detection is one of the fundamental steps in image processing, image analysis, image pattern recognition, and computer vision techniques. ... A-contrario line ...
In image processing, a Robinson compass mask is a type of compass mask used for edge detection. It has eight major compass orientations, [1] each will extract the edges in respect to its direction. A combined use of compass masks of different directions could detect the edges from different angles.
An edge in an image may point in a variety of directions, so the Canny algorithm uses four filters to detect horizontal, vertical and diagonal edges in the blurred image. The edge detection operator (such as Roberts, Prewitt, or Sobel) returns a value for the first derivative in the horizontal direction (G x) and the vertical direction (G y ...
In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.
Technically, it is a discrete differentiation operator, computing an approximation of the gradient of the image intensity function. At each point in the image, the result of the Sobel–Feldman operator is either the corresponding gradient vector or the norm of this vector. The Sobel–Feldman operator is based on convolving the image with a ...
Feature detection is a low-level image processing operation. That is, it is usually performed as the first operation on an image and examines every pixel to see if there is a feature present at that pixel. If this is part of a larger algorithm, then the algorithm will typically only examine the image in the region of the features.
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.
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