By Petra Perner, Ovidio Salvetti
This e-book constitutes the refereed lawsuits of the overseas convention on Mass facts research of signs and pictures in medication, Biotechnology and Chemistry, MDA 2006 and 2007, held in Leipzig, Germany..
The themes contain innovations and advancements of sign and picture generating strategies, item matching and item monitoring in microscopic and video microscopic photos, 1D, second and 3D form research, description and have extraction of texture, constitution and site, photograph segmentation algorithms, parallelization of photo research and semantic tagging of pictures from existence technology applications.
Read or Download Advances in Mass Data Analysis of Signals and Images in Medicine, Biotechnology and Chemistry: International Conference, MDA 2006/2007, PDF
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408–422. Springer, Heidelberg (2002) 11. : Morphological Image Analysis – Principles and Applications, 2nd edn. Springer, Heidelberg (2003) 12. : An analysis of topological properties of digitized binary pictures using local features. Comput. Graphics Image Process. 4, 63–73 (1975) 13. : Detecting foreground components in grey level images for shift invariant and topology preserving pyramids. , Kamel, M. ) ICIAR 2004. LNCS, vol. 3211, pp. 57–64. Springer, Heidelberg (2004) 14. : Grey level image components for multi-scale representation.
Ramella and G. Sanniti di Baja Fig. 4. Top: the 128×128 image, left, and its 64×64 lower resolution representation, right. Bottom: the components found at the end of the process for the 128×128 image, left, and the 64×64 image, right. Fig. 5. The segmentation obtained for the running example In Fig. 5, the segmentation of the running example is shown. The white lines, superimposed on the original image, identify the borders of the components of the foreground that have been singled out. 3 Extending the Method to Color Images In this section, we briefly discuss a possible way to extend our method to color images.
If the objects perceived in the input image by the expert have large size, a quite lower resolution will still reasonably reflect the properties of G and the most important components will still be those detected at the low resolution representation. Of course, if G includes small size foreground components, resorting to a very low resolution image is not advisable, since the input image would be represented in a too coarse way. For the running example, we consider the image G’ with resolution 64×64 pixels as adequate to the aim.