Edge and Corners

Edge

aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The points at which image brightness changes sharply are typically organized into a set of curved line segments termed edges. Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature extraction^[1]. Most of the edge detection algorithms has been implemented in CVIPtools.

The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images.The Canny algorithm is adaptable to various environments. Its parameters allow it to be tailored to recognition of edges of differing characteristics depending on the particular requirements of a given implementation. it is often suggested to use Rachid Deriche's infinite impulse response form of Canny's filter (the Canny–Deriche detector), which is recursive, and which can be computed in a short, fixed amount of time for any desired amount of smoothing. The second form is suitable for real time implementation.
Deriche edge detector  a multistep algorithm used to obtain an optimal result of edge detection in a discrete two-dimensional image.
 Sobel operator & Prewitt operator

Edge Detection Techniques: Evaluations and Comparisons

http://www.m-hikari.com/ams/ams-password-2008/ams-password29-32-2008/nadernejadAMS29-32-2008.pdf


Real-Time Canny Edge Detection Parallel Implementation for FPGAs
The Canny edge detector is the most implemented edge detection algorithm because of its ability to detect edges even in images that are intensely contaminated by noise. However, this is a time consuming algorithm and therefore its implementations are difficult to reach real time response speeds. Especially nowadays where the demand for high resolution image processing is constantly increasing, the need for fast and efficient edge detector implementations is ever so present. A new parallel Canny edge detector FPGA implementation is proposed in this paper to answer this demand. The Canny edge detector is the most implemented edge detection algorithm because of its ability to detect edges even in images that are intensely contaminated by noise. However, this is a time consuming algorithm and therefore its implementations are difficult to reach real time response speeds. Especially nowadays where the demand for high resolution image processing is constantly increasing, the need for fast and efficient edge detector implementations is ever so present. A new parallel Canny edge detector FPGA implementation is proposed in this paper to answer this demand.

Corner   

Corner detection is an approach used within computer vision systems to extract certain kinds of features and infer the contents of an image. Corner detection is frequently used in motion detection, image registration, video tracking. Corner detection overlaps with the topic of interest point detection.

The Harris & Stephens / Plessey / Shi–Tomasi corner detection algorithm

http://www.aishack.in/2010/04/harris-corner-detector/

FAST Corner Detection

http://www.edwardrosten.com/work/fast.html