In this paper we focus on the problem of automatically registering dermatological images, because even if different products are available, most of them share the problem of a limited field of view on the skin. A possible solution is then the composition of multiple takes of the same lesion with digital software, such as that for panorama images creation.In this work, to perform an automatic selection of matching points the Harris Corner Detector is used, and to cope with outlier couples we employed the RANSAC method. Projective mapping is then used to match the two images. Given a set of correspondence points, Singular Value Decomposition was used to compute the transform parameters.At this point the two images need to be blended together. One initial assumption is often implicitly made: the aim is to merge two rectangular images. But when merging occurs between more than two images iteratively, this assumption will fail. To cope with differently shaped images, we employed the Distance Transform and provided a weighted merging of images. Different tests were conducted with dermatological images, both with standard rectangular frame and with not typical shapes, as for example a ring due to the objective and lens selection. The successive composition of different circular images with other blending functions, such as the Hat function, doesn’t correctly get rid of the border and residuals of the circular mask are still visible. By applying Distance Transform blending, the result produced is insensitive of the outer shape of the image.

Distance transform for automatic dermatologic images composition / Grana, Costantino; Pellacani, Giovanni; Seidenari, Stefania; Cucchiara, Rita. - STAMPA. - 6144:(2006), pp. 2U1-2U9. ((Intervento presentato al convegno Medical Imaging 2006: Image Processing tenutosi a San Diego, California, USA nel Feb 13-16.

Distance transform for automatic dermatologic images composition

GRANA, Costantino;PELLACANI, Giovanni;SEIDENARI, Stefania;CUCCHIARA, Rita
2006

Abstract

In this paper we focus on the problem of automatically registering dermatological images, because even if different products are available, most of them share the problem of a limited field of view on the skin. A possible solution is then the composition of multiple takes of the same lesion with digital software, such as that for panorama images creation.In this work, to perform an automatic selection of matching points the Harris Corner Detector is used, and to cope with outlier couples we employed the RANSAC method. Projective mapping is then used to match the two images. Given a set of correspondence points, Singular Value Decomposition was used to compute the transform parameters.At this point the two images need to be blended together. One initial assumption is often implicitly made: the aim is to merge two rectangular images. But when merging occurs between more than two images iteratively, this assumption will fail. To cope with differently shaped images, we employed the Distance Transform and provided a weighted merging of images. Different tests were conducted with dermatological images, both with standard rectangular frame and with not typical shapes, as for example a ring due to the objective and lens selection. The successive composition of different circular images with other blending functions, such as the Hat function, doesn’t correctly get rid of the border and residuals of the circular mask are still visible. By applying Distance Transform blending, the result produced is insensitive of the outer shape of the image.
Medical Imaging 2006: Image Processing
San Diego, California, USA
Feb 13-16
6144
2U1
2U9
Grana, Costantino; Pellacani, Giovanni; Seidenari, Stefania; Cucchiara, Rita
Distance transform for automatic dermatologic images composition / Grana, Costantino; Pellacani, Giovanni; Seidenari, Stefania; Cucchiara, Rita. - STAMPA. - 6144:(2006), pp. 2U1-2U9. ((Intervento presentato al convegno Medical Imaging 2006: Image Processing tenutosi a San Diego, California, USA nel Feb 13-16.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/464374
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