Deep dictionary learning application in GPR B-scan images

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 con...

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Bibliographic Details
Published in:Signal, image and video processing image and video processing, 2018-11, Vol.12 (8), p.1567-1575
Main Authors: Ozkaya, Umut, Seyfi, Levent
Format: Article
Language:English
Subjects:
Algorithms
Classifiers
Computer Imaging
Computer Science
Dictionaries
Image Processing and Computer Vision
Land mines
Machine learning
Multimedia Information Systems
Object recognition
Original Paper
Pattern Recognition and Graphics
Signal,Image and Speech Processing
Vision
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Summary: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%.
ISSN:1863-1703
1863-1711
DOI:10.1007/s11760-018-1313-x