Authors:
Lars Libuda
;
Ingo Grothues
and
Karl-Friedrich Kraiss
Affiliation:
Chair of Technical Computer Science, Aachen University, Germany
Keyword(s):
Ellipse Detection, Shape Analysis & Representation, Image Analysis.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Segmentation and Grouping
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Ellipse detection is an important task in vision based systems because many real world objects can be described by this primitive. This paper presents a fast data driven four stage filtering process which uses geometric features in each stage to synthesize ellipses from binary image data with the help of lines, arcs, and extended arcs. It can cope with partially occluded and overlapping ellipses, works fast and accurate and keeps memory consumption to a minimum.