Titlebook: Image Analysis; 14th Scandinavian Co Heikki Kalviainen,Jussi Parkkinen,Arto Kaarna Conference proceedings 2005 Springer-Verlag GmbH Germany

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Feature Extraction for Oil Spill Detection Based on SAR Imagested results. Both traditional region descriptors, features tailored to oil spill detection and techniques originally associated with other applications are evaluated. Experimental results show an increase from 89% to 97% in the number of suspected oil spills detected.

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Biometric Recognition: How Do I Know Who You Are?services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user, and not anyone else. Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones and ATMs. In the absence of robust person recognitio

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Paving the Way for Image Understanding: A New Kind of Image Decomposition Is Desiredcognition tasks. Generally image understanding assumes interplay of two sub-processes: image information content discovery and image information content interpretation. Despite of its widespread use, the notion of “image information content” is still ill defined, intuitive, and ambiguous. Most often

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Levelset and B-Spline Deformable Model Techniques for Image Segmentation: A Pragmatic Comparative Sttween some deformable model methods have already been published [1]. Yet, very few experimental comparative studies on real data have been reported. In this paper, we compare a levelset with a B-spline based deformable model approach in order to understand the mechanisms involved in these widely use

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Steerable Semi-automatic Segmentation of Textured Imagesand textured images. The main contribution lies in incorporating new functions handling colour and texture information into the graph representing an image, since the previous method works for grayscale images only. The suggested method is semi-automatic since the user provides additional constraint

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