Terrain classification based on 3D co-occurrence features

Authors:
Dong-Min Woo;Dong-Chul Park;Young-Soo Song;Quoc-Dat Nguyen;Quang-Dung Nguyen Tran
Affiliations:
Department of Information Engineering, Myong Ji University, Gyeonggido, Korea;Department of Information Engineering, Myong Ji University, Gyeonggido, Korea;Department of Information Engineering, Myong Ji University, Gyeonggido, Korea;Department of Information Engineering, Myong Ji University, Gyeonggido, Korea;Department of Information Engineering, Myong Ji University, Gyeonggido, Korea
Venue:
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Year:
2007

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Abstract

This paper suggests 3D co-occurrence texture features by extending the concept of co-occurrence feature to the 3D world. The suggested 3D features are described as a 3D co-occurrence matrix by using a co-occurrence histogram of digital elevations at two contiguous positions. With the addition of 3D co-occurrence features, we encounter the high dimensionality problem in the classification process. Since these ANN (Artificial Neural Networks) clustering algorithms are known as robust in this situation, FCM (Fuzzy C-mean) and GBFCM (Gradient Based Fuzzy C-mean) clustering algorithms are employed to implement the terrain classifier. Experimental results show that the classification accuracy with the addition of 3D co-occurrence features is significantly improved over the conventional classification method only with 2D features.