Multimedia systems often use various detection methods to track relevant objects in images and video frames. The tracking scheme is often based on capturing of significant points in the object, which are used by implemented methods to extract the shape, dimensions, etc. and then further process these information. In recent years many advances in Computational Intelligence methods and approaches have been reported. Therefore the question has arisen if these, i.e. heuristics, are applicable to multimedia tracking systems? This article is to discuss developed heuristic methods for Key-Points tracking and shape extraction. In the following sections of this work developed approaches, in particular a dedicated Cuckoo Search Algorithm and Firefly Algorithm versions, are presented and discussed in comparison to some classical methods to show potential advantages and disadvantages. Benchmark tests and experimental research results are presented to show efficacy and extraction precision on test images.

Graphic object feature extraction system based on Cuckoo Search Algorithm

NAPOLI, CHRISTIAN;TRAMONTANA, EMILIANO ALESSIO
2016-01-01

Abstract

Multimedia systems often use various detection methods to track relevant objects in images and video frames. The tracking scheme is often based on capturing of significant points in the object, which are used by implemented methods to extract the shape, dimensions, etc. and then further process these information. In recent years many advances in Computational Intelligence methods and approaches have been reported. Therefore the question has arisen if these, i.e. heuristics, are applicable to multimedia tracking systems? This article is to discuss developed heuristic methods for Key-Points tracking and shape extraction. In the following sections of this work developed approaches, in particular a dedicated Cuckoo Search Algorithm and Firefly Algorithm versions, are presented and discussed in comparison to some classical methods to show potential advantages and disadvantages. Benchmark tests and experimental research results are presented to show efficacy and extraction precision on test images.
2016
Artificial intelligence; Image processing; Feature extraction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/39914
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