.png){kind=icon}
.png){kind=icon}
Return
Circle detection on images using genetic algorithms
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patrec.2005.10.003.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we present a circle detection method based on genetic algorithms. Our genetic algorithm uses the encoding of three edge points as the chromosome of candidate circles (x, y, r) in the edge image of the scene. Fitness function evaluates if these candidate circles are really present in the edge image. Our encoding scheme reduces the search space by avoiding trying unfeasible individuals, this results in a fast circle detector. Our approach detects circles with sub-pixellic accuracy on synthetic images. Our method can also detect circles on natural images with sub-pixellic precision. Partially occluded circles can be located in both synthetic and natural images. Examples of the application of our method to the recognition of hand-drawn circles are also shown. Detection of several circles in a single image is also handled by our method. (c) 2005 Elsevier B.V. All rights reserved.
Keywords:
object recognition
circle detection
genetic algorithms
hand-drawn shape location
Journal
IF:
3.3
Papers:
7.9K
Citations:
1.6W
Organization
No organization information available