Feature detection (computer vision): Difference between revisions

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== Types of image features ==
 
=== [[Edge_detection|Edges]] ===
 
These are points where there is a boundary (or edge) between two image regions. In general, the edge can be of an arbitrary shape, and may include junctions. In practice, edges are usually defined as points in the image which have a strong [[gradient]]. Furthermore, some common algorithms will then chain high gradient points together to form a more complete description of an edge. These algorithms may place some constraints on the shape of an edge.
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These terms are used somewhat interchangeably and refer to point-like features in an image, which have a local two dimensional structure. The name "Corner" arose since early algorithms first performed edge detection, and then analysed the edges to find rapid changes in direction (corners). These algorithms were then developed so that explicit edge detection was no longer required, for instance by looking for high levels of [[curvature]] in the image gradient. It was then noticed that the so-called corners were also being detected on parts of the image which were not corners in the traditional sense (for instance a small bright spot on a dark background may be detected). These points are frequently known as interest points, but the term "corner" is used by tradition.
 
 
=== [[Blob_detection|Blobs / Regions of interest or interest points]] ===