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Various approaches have been proposed in the literature for texture characterization of images. Some of them are based on statistical properties, others on fractal measures and some more on multi-resolution analysis. Basically, these approaches have been applied on mono-band images. However, most of them have been extended by including the additional(More)
This paper deals with the development of a new texture analysis method based on both spatial and spectral information for texture classification purposes. The idea of Generalized Gray Level Difference Method (GGLDM) is to extend the concept of spatial Gray Level Difference Method(GLDM) by assuming texture joint information between spectral bands. In(More)
In this paper, we present a new approach for multi-spectral texture classification. Therefore, we aim to add spectral information to classical texture analysis methods that only treat gray-level spatial variations. To achieve this goal, we propose a Spatial and Spectral Gray Level Dependence Method (SSGLDM) in order to extend the concept of spatial gray(More)
This paper deals with the development of a new texture analysis method based on both spatial and spectral information for texture classification purposes. The idea of the Spatial and Spectral Gray Level Dependence Method (SSGLDM) is to extend the concept of spatial gray level dependence method by assuming texture joint information between spectral bands. In(More)
Automatic robot / Computed Tomography (CT) scanner registration is an important feature for robot-assisted percutaneous needle placement under CT-scanner. This registration can be done using 3D images, but for fast, low X-ray radiation it is interesting to be able to perform the registration with a single slice. In this paper, a new marker is proposed,(More)
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