Several papers addressed ellipse detection as a first step for several computer vision applications, but most of the proposed solutions are too slow to be applied in real time on large images or with limited hardware resources. This paper presents a novel algorithm for fast and effective ellipse detection and demonstrates its superior speed performance on large and challenging datasets. The proposed algorithm relies on an innovative selection strategy of arcs which are candidate to form ellipses and on the use of Hough transform to estimate parameters in a decomposed space. The final aim of this solution is to represent a building block for new generation of smart-phone applications which need fast and accurate ellipse detection also with limited computational resources. © 2014 Elsevier Ltd.

A fast and effective ellipse detector for embedded vision applications / Fornaciari, M.; Prati, A.; Cucchiara, R.. - In: PATTERN RECOGNITION. - ISSN 0031-3203. - 47:11(2014), pp. 3693-3708. [10.1016/j.patcog.2014.05.012]

A fast and effective ellipse detector for embedded vision applications

Cucchiara R.
2014

Abstract

Several papers addressed ellipse detection as a first step for several computer vision applications, but most of the proposed solutions are too slow to be applied in real time on large images or with limited hardware resources. This paper presents a novel algorithm for fast and effective ellipse detection and demonstrates its superior speed performance on large and challenging datasets. The proposed algorithm relies on an innovative selection strategy of arcs which are candidate to form ellipses and on the use of Hough transform to estimate parameters in a decomposed space. The final aim of this solution is to represent a building block for new generation of smart-phone applications which need fast and accurate ellipse detection also with limited computational resources. © 2014 Elsevier Ltd.
2014
47
11
3693
3708
A fast and effective ellipse detector for embedded vision applications / Fornaciari, M.; Prati, A.; Cucchiara, R.. - In: PATTERN RECOGNITION. - ISSN 0031-3203. - 47:11(2014), pp. 3693-3708. [10.1016/j.patcog.2014.05.012]
Fornaciari, M.; Prati, A.; Cucchiara, R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1247295
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