Landmine detection using IR image segmentation by means of fractal dimension analysis

Horacio A. Abbate; Juliana Gambini; Claudio Delrieux; Eduardo H. Castro

doi:10.1117/12.819150

4 May 2009 Landmine detection using IR image segmentation by means of fractal dimension analysis

Horacio A. Abbate, Juliana Gambini, Claudio Delrieux, Eduardo H. Castro

Proceedings Volume 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV; 730317 (2009) https://doi.org/10.1117/12.819150
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

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.

Citation Download Citation

Horacio A. Abbate, Juliana Gambini, Claudio Delrieux, and 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); https://doi.org/10.1117/12.819150

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