Textured image segmentation using autoregressive model and artificial neural network

doi:10.1016/0031-3203(95)00051-8

Pattern Recognition

Volume 28, Issue 12, December 1995, Pages 1807-1817

https://doi.org/10.1016/0031-3203(95)00051-8 Get rights and content

Abstract

In this paper, we use a two-dimensional (2-D) AR model for texture description. The coefficients of the AR model as the parameters can thus be used to identify textured images. These processes are ideally suited to implementation by neural networks which are well known for their parallel execution and adaptive learning abilities. The proposed network consists of three subnets, namely the input subnet (ISN), the analysis subnet (ASN) and the classification subnet (CSN), respectively. The neural network obtains parameters for a 2-D AR model on a given texture through an adaptive learning procedure, and segments an input image into regions with the learned textures. Furthermore, a textured image which has a certain degree of deformation with respect to one of the possible texture classes can be correctly classified by the network. The network is easy to extend because of its modular structure in which all channels work independently. A region growing technique for texture segmentation is implemented by comparing local region properties. It is able to grow all regions in a textured image simultaneously starting from initially decided internal regions until smooth boundaries are formed between all adjacent regions. The performance of the proposed network has been examined on real textured images. In the classification phase, images proceed through the network without the preprocessing and feature extraction required by many other techniques. Hence, overall computation time has been considerably reduced.

Section snippets

bio1About the Author—SI WEI LU was born in Jiansu, China. He graduated from Electrical Engineering Department Tsinghua University, Peking, China, in 1967, and received the M.S. and Ph.D. degrees in Department of Systems Design Engineering from the University of Waterloo in 1982 and 1986, respectively. He was visiting Assistant Professor in the Department of Computer Science, Concordia University Montreal Canada. He is Associate Professor in the Department of Computer Science, Memorial

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bio2About the Author—HE XU received her B.Sc from Beijing Natural Science and Engineering University, China, in 1983, and received the M.S. degree from the Department of Computer Science at Memorial University, St. John's Canada, in 1994. From 1986 to 1990 she has worked at the Institute of Intelligent Machines, Academia Sinica, Hefei, China. Her research interests are computer vision, neural networks and pattern recognition

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Textured image segmentation using autoregressive model and artificial neural network

Abstract

Section snippets

Pattern Recognition

Pattern Recognition

Pattern Recognition

Statistical and structural approaches to texture

Proc. IEEE

Estimation and choice of neighbors in spatial-interaction models of images

IEEE Trans. Inf. Theory