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Deep dictionary learning application in GPR B-scan images

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Abstract

This paper introduces GPR B-scan database which contains 180 labelled images to facilitate research in developing presentation algorithm for this challenging scenario. Along with GPR B-scan images, there are several other detections of buried objects that are explored in the literature. The next contribution of this research is a novel multilevel deep dictionary learning-based presentation buried object detection algorithm that can discern different kinds of materials. An efficient layer by layer training approach is formulated to learn the deep dictionaries followed by different classifiers as types of shape for buried objects. By changing the number of layers in proposed algorithm, performances in different classifiers are compared. It is possible to integrate the proposed algorithm with real-time systems because it is supervised and has high classification accuracy with 94.4%.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Selcuk University, 42075, Konya, Turkey

    Umut Ozkaya & Levent Seyfi

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  1. Umut Ozkaya
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  2. Levent Seyfi
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Correspondence to Umut Ozkaya.

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Ozkaya, U., Seyfi, L. Deep dictionary learning application in GPR B-scan images. SIViP 12, 1567–1575 (2018). https://doi.org/10.1007/s11760-018-1313-x

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  • DOI: https://doi.org/10.1007/s11760-018-1313-x

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