Real time image segmentation using an adaptive thresholding approach

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Title: Real time image segmentation using an adaptive thresholding approach
Authors: Arques Corrales, Pilar | Aznar Gregori, Fidel | Pujol, Mar | Rizo, Ramón
Research Group/s: Informática Industrial e Inteligencia Artificial
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Region segmentation | Adaptive thresholding | Simulated annealing | Real time | Markov Random Field
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Date Created: 2006
Issue Date: Nov-2006
Publisher: Springer
Citation: ARQUES CORRALES, Pilar, et al. “Real time image segmentation using an adaptive thresholding approach”. Lecture notes in computer science. 2006, vol. 4177/2006. ISSN 0302-9743, pp. 389-398
Abstract: The aim of image segmentation is the partition of the image in homogeneous regions. In this paper we propose an approximation based on Markov Random Fields (MRF) able to perform correct segmentation in real time using colour information. In a first approximation a simulated annealing approach is used to obtain the optimal segmentation. This segmentation will be improved using an adaptive threshold algorithm, to achieve real time. The experiment results using the proposed segmentation prove its correctness, both for the obtained labelling and for the response time.
Sponsor: Proyecto de la Generalitat Valenciana GV04B685
ISSN: 0302-9743
DOI: 10.1007/11881216
Language: eng
Type: info:eu-repo/semantics/article
Rights: The original publication is available at
Peer Review: si
Publisher version:
Appears in Collections:INV - i3a - Artículos de Revistas

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