Computer-augmented detection of targets generally refers to the localization of potential targets by computer processing of data from a variety of sensors. Automatic detection is applicable for data reduction purposes in the reconnaissance domain and is therefore aimed at reducing the workload for human operators with respect to activities such as to targeting individual targets on large areas or volumes for assessing the battlefield/battlespace situation. An increase of reliability and efficiency is expected. The results of automatic image evaluation are offered to the image analyst as hypotheses. In this paper image sequences from an infrared (IR) sensor (spectral range 3-5 mu m) are analyzed with the aim of finding Regions of Interest (ROIs), where the target-background segmentation is performed by means of blob evaluation. Also low contrast conditions can be successfully tackled if the directions of the gray value gradient are considered, which are nearly independent of the contrast. Blobs are generated by applying adaptive thresholds in the ROIs. Here the evaluation of histograms is very important for the extraction of structured features. It is assumed that the height, aspect angle, and camera parameters are approximately known for an estimation of target sizes in the image domain. This estimation yields important parameters for the target/clutter discrimination.
Computer-augmented detection of targets in cluttered and low-contrast backgrounds
1997
6 Seiten, 3 Quellen
Conference paper
English
Computer-augmented detection of targets in cluttered and low-contrast backgrounds [3062-45]
British Library Conference Proceedings | 1997
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