A New Algorithm for Ball Recognition using Circle Hough Transform and Neural Classifier (Articolo in rivista)

Type
Label
  • A New Algorithm for Ball Recognition using Circle Hough Transform and Neural Classifier (Articolo in rivista) (literal)
Anno
  • 2004-01-01T00:00:00+01:00 (literal)
Alternative label
  • T. D’Orazio, M. Leo, A. Distante (2004)
    A New Algorithm for Ball Recognition using Circle Hough Transform and Neural Classifier
    in Pattern recognition
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • T. D’Orazio, M. Leo, A. Distante (literal)
Pagina inizio
  • 393 (literal)
Pagina fine
  • 408 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 37 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • C. Guaragnella - DEE, Electrotechnology and Electronics Dept. Politecnico di Bari (literal)
Titolo
  • A New Algorithm for Ball Recognition using Circle Hough Transform and Neural Classifier (literal)
Abstract
  • A large number of methods for circle detection have been studied in the last years for several image processing applications. The context application considered in this work is the soccer game. In the sequences ofsoccer images it is very important to identify the ball in order to verify the goal event. This domain is a challenging one as a great number of problems have to be faced, such as occlusions, shadows, objects similar to the ball, real-time processing and so on. In this work a visual framework trying to solve the above-stated problems, mainly considering real-time computational aspects, has been developed. The ball detection algorithm has to be very simple in terms oftime processing and also has to be effcient in terms off false positive rate. Our framework consists of two sequential steps for solving the ball recognition problem: the frst step uses a modifed version of the directional circle Hough transform to detect the region ofthe image that is the best candidate to contain the ball; in the second step a neural classifier is applied on the selected region to confirm if the ball has been properly detected or a false positive has been found. Some tricks like background subtraction and ball tracking have been applied in order to maintain the search ofthe ball only in limited areas ofthe image. Different light conditions have been considered as they introduce strong modifications on the appearance ofthe ball in the image: when the image sequences are taken with natural light, as the light source is strictly directional, the ball, due to self-shades, appears as a spherical cap; this case has been taken in account and the search ofthe ball has been modified in order to manage this situation. A large number ofexperiments have been carried out showing that the proposed method obtains a high detection score. (literal)
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