Applying distance histograms for robust object recognition

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Title: Applying distance histograms for robust object recognition
Authors: Arques Corrales, Pilar | Pujol, Francisco A. | Llorens Largo, Faraón | Pujol, Mar | Rizo, Ramón
Research Group/s: Informática Industrial e Inteligencia Artificial | Informática Industrial y Redes de Computadores
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial | Universidad de Alicante. Departamento de Tecnología Informática y Computación
Keywords: Cybernetics | Image processing | Markov processes
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: Jan-2007
Publisher: Emerald Group Publishing Limited
Citation: ARQUES CORRALES, Pilar, et al. “Applying distance histograms for robust object recognition”. Kybernetes. 2007, Vol. 36, No. 1. ISSN 0368-492X, pp. 42-51
Abstract: One of the main goals of vision systems is to recognize objects in real world to perform appropriate actions. This implies the ability of handling objects and, moreover, to know the relations between these objects and their environment in what we call scenes. Most of the time, navigation in unknown environments is difficult due to a lack of easily identifiable landmarks. Hence, in this work, some geometric features to identify objects are considered. Firstly, a Markov random field segmentation approach is implemented. Then, the key factor for the recognition is the calculation of the so-called distance histograms, which relate the distances between the border points to the mass center for each object in a scene.
Sponsor: This work has been supported by the Conselleria d’Empresa, Universitat i Ciència, of the Generalitat Valenciana, project number GV04B685.
ISSN: 0368-492X
DOI: 10.1108/03684920710741134
Language: eng
Type: info:eu-repo/semantics/article
Peer Review: si
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Appears in Collections:INV - i3a - Artículos de Revistas

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