4 May 2009 Landmine detection using IR image segmentation by means of fractal dimension analysis
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Abstract
This work is concerned with buried landmines detection by long wave infrared images obtained during the heating or cooling of the soil and a segmentation process of the images. The segmentation process is performed by means of a local fractal dimension analysis (LFD) as a feature descriptor. We use two different LFD estimators, box-counting dimension (BC), and differential box counting dimension (DBC). These features are computed in a per pixel basis, and the set of features is clusterized by means of the K-means method. This segmentation technique produces outstanding results, with low computational cost.
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Horacio A. Abbate, Horacio A. Abbate, Juliana Gambini, Juliana Gambini, Claudio Delrieux, Claudio Delrieux, Eduardo H. Castro, Eduardo H. Castro, } "Landmine detection using IR image segmentation by means of fractal dimension analysis", Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 730317 (4 May 2009); doi: 10.1117/12.819150; https://doi.org/10.1117/12.819150
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