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Tag: Edge Detection
Want to understand how computers ‘see’ objects in images? Edge detection is a key process! This section explores different methods, like gradient detection and non-maximum suppression, used to identify object boundaries in images.
Unlock the power of edge detection and explore its applications in the vast world of computer vision!
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Prewitt operator for edge detection
The Prewitt operator is one of the first algorithms for edge detection by gradient transform. It is developed by Judith M. S. Prewitt and is a popular tool for image analysis.
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Harris Corner Detector: How to find key-points in pictures
Harris Corner Detector is a popular computer vision algorithm used to detect key points in images and video. Corners are important features of the image, as they provide useful information for detecting objects and scenes.
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Gradient Non-Maximum Suppression
Gradient non-maximum suppression is an edge thinning algorithm that extracts thin contours of objects in an image. The output of this image processing algorithm is contour curves that are one pixel wide. Non-maximal suppression is…
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Sobel-Feldman filter: Edge Detection and Gradient Extraction
The Sobel filter (also called Sobel-Feldman operator) is an edge detection algorithm, that results in image emphasizing edges. Computer vision apps often use this image processing technique to extract the objects contours.
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Median Filter – Edge Preserving Filter Tutorial
The Median filter is a nonlinear noise reduction technique that is widely used in image processing. It is very effective in cases of salt and paper noise (impulsive noise) and speckle noise. However, in cases…
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Hough Transform – Basic Shape Detection
The Hough Transform is a method to find shapes in an image. The classical transformation is initially designed to identify lines in the image. Later the transform extends to identify different kind of shapes such…
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