Automatic Detection and Classification of Buried Objects in GPR Images Using Genetic Algorithms and Support Vector Machines

@article{Pasolli2008AutomaticDA,
  title={Automatic Detection and Classification of Buried Objects in GPR Images Using Genetic Algorithms and Support Vector Machines},
  author={Edoardo Pasolli and Farid Melgani and Massimo Donelli and Redha Attoui and Mariette de Vos},
  journal={IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium},
  year={2008},
  volume={2},
  pages={II-525-II-528}
}
This work presents a novel pattern recognition approach for the automatic analysis of ground penetrating radar (GPR) images. The developed system comprises pre-processing, segmentation, object detection and material recognition stages. Object detection is done using an innovative unsupervised strategy based on genetic algorithms (GA) that allows to localize linear/hyperbolic patterns in GPR images. Object material recognition is approached as a classification issue, which is solved by means of… CONTINUE READING