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!

Posts Collection

Prewitt Operator for Edge Detection

In the realm of image processing, the ability to detect edges is crucial for understanding and interpreting visual information. Among the pioneering techniques that have… Learn More

In: Image Processing
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,… Learn More

In: Image Processing
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… Learn More

In: Image Processing
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… Learn More

In: Image Processing
Median Filter: A Guide to Edge Preserving Blur

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… Learn More

In: Image Processing
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… Learn More

In: Image Processing