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Advances in Artificial Intelligence
Volume 2012 (2012), Article ID 512159, 12 pages
Research Article

Soccer Ball Detection by Comparing Different Feature Extraction Methodologies

Istituto di Studi sui Sistemi Intelligenti per l'Automazione, CNR, Via G. Amendola 122/D, 70126 Bari, Italy

Received 30 May 2012; Accepted 26 August 2012

Academic Editor: Djamel Bouchaffra

Copyright © 2012 Pier Luigi Mazzeo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a comparison of different feature extraction methods for automatically recognizing soccer ball patterns through a probabilistic analysis. It contributes to investigate different well-known feature extraction approaches applied in a soccer environment, in order to measure robustness accuracy and detection performances. This work, evaluating different methodologies, permits to select the one which achieves best performances in terms of detection rate and CPU processing time. The effectiveness of the different methodologies is demonstrated by a huge number of experiments on real ball examples under challenging conditions.