Title: Combination of a 2D-RCA model and ANNs for texture image segmentation

Authors: Assia Ayache; Soumia Kharfouchi; Fouad Rahmani

Addresses: Department of Mathematics, Mentouri University, Constantine, 25000, Algeria ' Faculty of Medicine, Salah Boubnider University, Constantine, 25000, Algeria ' Ecole Biotechnique, Salah Boubnider University, Constantine, 25000, Algeria

Abstract: In this paper, a region growing technique is used to achieve image segmentation by merging some starting points or internal small areas if they are homogeneous according to a measurement of a local region property. A 2D random coefficients autoregressive model (2D RCA) is fitted. First, an estimation procedure using a generalised method of moments (GMM) technique is proposed to extract some local region properties. For this, a gradient-based neural network (GNN) is used to estimate the 2D RCA model parameters from a given texture. The cost function of the proposed GNN is based on a strong matching of the statistical moments of the corresponding 2D-RCA model and the sample moments of population image data. Experimental results demonstrate the effectiveness and the relevance of the proposed method.

Keywords: image segmentation; 2D RCA models; ANNs; artificial neural networks; GMM; generalised method of moments; spatial statistic; 2D stochastic processes; non linear spatial models; stationarity; statistical learning.

DOI: 10.1504/IJCSM.2022.124691

International Journal of Computing Science and Mathematics, 2022 Vol.15 No.3, pp.289 - 300

Received: 27 Jan 2020
Accepted: 25 Jun 2020
Published online: 08 Aug 2022 *

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