Unsupervised segmentaiton of subsurface radar images

Waleed Al-Nuaimy; Yi Huang; S. Shihab; Asger Eriksen

doi:10.1117/12.462233

12 April 2002 Unsupervised segmentaiton of subsurface radar images

Waleed Al-Nuaimy, Yi Huang, S. Shihab, Asger Eriksen

Proceedings Volume 4758, Ninth International Conference on Ground Penetrating Radar; (2002) https://doi.org/10.1117/12.462233
Event: Ninth International Conference on Ground Penetrating Radar (GPR2002), 2002, Santa Barbara, CA, United States

Abstract

The volume of image data generated in ground-penetrating radar surveys can severely restrict the practicality of this site investigation technique. This is particularly true in situations where automatic analysis or interpretation is required, as segmentation and classification tasks that utilise multivariate data are critically affected by the volume and dimensionality of the data. A general-purpose unsupervised image segmentation system is presented here for the automatic detection of image regions exhibiting different visual texture properties. A suboptimal feature selection procedure is proposed to automatically select the set of texture features best suited for the particular application. The reduction in the size of the feature set both reduces the computation time and improves the accuracy of the final classification.

Citation Download Citation

Waleed Al-Nuaimy, Yi Huang, S. Shihab, and Asger Eriksen "Unsupervised segmentaiton of subsurface radar images", Proc. SPIE 4758, Ninth International Conference on Ground Penetrating Radar, (12 April 2002); https://doi.org/10.1117/12.462233

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