engleski

Segmentation of the aerial RGB images of Suspected Hazardous Area for the needs of Non-technical Survey

In the mine action community, Non-Technical Survey is implemented to provide information for better spatial definition of mine or explosive remnants of war contamination. Airborne and spaceborne surveys of wider Suspected Hazardous Area (SHA) regions are often executed to collect information about physical changes and circumstances that may be employed in the subsequent technical interventions. Simple electro-optical sensors which acquire data from the visible part of electromagnetic spectrum, like DSLR or SLR cameras, can be used for this kind of surveys. These aerial RGB images are then inspected by trained human photo (mine scene) interpreter who is familiar with the military doctrine and specific characteristics of the conflict. Mine scene interpreter seeks for the indicators of mine presence and absence. Novel image processing techniques could provide benefits to the standard photointerpretation workflow by making it more efficient. Geographic object-based image analysis (GEOBIA) is one of them. The idea of GEOBIA is to process georeferenced images at the object level, as the entities found in the environment are usually objects (or grouped pixels) instead of single pixels. This approach enables analysis of spatial relations and geometrical object parameters. The main step influencing the GEOBIA results is the quality of image segmentation. In this paper, results of more image segmentation algorithms are tested on the color aerial images of SHA and images of exploded ammunition depot in the Croatia. Acquired results are discussed, while potential and constraints of image segmentation for application in the Non-technical survey are underlined.

humanitarian demining, non-technical survey, indicators of mine presence, GEOBIA, segmentation

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