Temporal analysis for land mine detection

Linderhead, A.; Sjökvist, Stefan; Nyberg, Sten; Uppsäll, Magnus; Grönwall, Christina; Andersson, Pierre; Letalick, Dietmar

doi:10.1109/ispa.2005.195443

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“…Sensor data are co-registered to pixel-correspondence. Earlier work of this approach has been reported in [7,6]. Our segmentation approach is described in Section 2.…”

Section: Introductionmentioning

confidence: 99%

Target Segmentation in Scenes with Diverse Background

Grönwall

Tolt

2011

Image Analysis

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Abstract. We propose a target segmentation approach based on sensor data fusion that can deal with the problem of a diverse background. Features from sensor images, including data from a laser scanner and passive sensors (cameras), are analyzed using Gaussian mixture estimation. The approach tackles some of the difficulties with Gaussian mixtures, e.g., selecting the number of initial components and a good description of data in terms of the number of Gaussian components, and determining the relevant features for the current data set. The feature selection quality is analyzed on-line. We propose a criterion that determines the quality of the resulting clusters in terms of their respective spatial distribution. The output from the analysis is used for object-background segmentation. Segmentation examples of surface-laid mines in outdoor scenes are shown.

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“…Sensor data are co-registered to pixel-correspondence. Earlier work of this approach has been reported in [7,6]. Our segmentation approach is described in Section 2.…”

Section: Introductionmentioning

confidence: 99%