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Goal:

Our main goal is to create an environment dedicated to image processing, computer graphics and computer vision applied to images from different fields of experimental Physics.

Aplications:

The study of several patterns from different fields of physics requires many observations techniques. Image Processing, Image Analysis and Computer Vision plays an important role in the quantitative analysis of such patterns and in the interpretation of their spatial arrangements. In this project we are interested in different images from different kind of systems : cellular structures, bubble patterns, fiber structures, etc. The main image analysis are : grain and topological analysis, densitometry, pattern recognition, and many other that are system dependent. Patterns came for example from magnetic-films (magneto-optical observations of magnetics domains), metalurgy, numeric simulations, x-ray difraction, atomic-force microscopy, etc.
 
  • What's an Image (avaiable version in Portuguese only)
  • Image Processing : Methods and Analysis (avaiable version in Portuguese only - PDF file)
  • Dictionary of Therms (avaiable version in Portuguese only)
  • Color conversion Descriptions (under revision)
  • Directory of Microscopy Products and Services 
  • Image Processing for PC software List.
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    Edge detection of a grain structure: (a) Original Image of a FLi film (image from a atomic force microscope (AFM), of a FLi film - from A.O.Caride/CBPF). (b) Image after segmentation. The segmentation was done using mathematical morphology techniques (dilation followed by a watershed algorithm). Both images are superposed for best view. (c) Grain are individualized and labeled. Border grains are eliminated from the final image. (d) Histogram of area distribution function of the original image.

    Neighbor Analysis of a cellular structure: (a) Original image with an hexagonal organization of a magnetic bubble structure. (b) Image after a segmentation in different regions. In the image a label (color) is affected to each cell. There are no correlations between this colors. (c) Histogram of the Radial Distribution Function of the distances between cells. Using this technique one can show peaks of first, second, third, ... neighbors of the cellular structure. (d) Detection of on cell in red and its6 neighbors in yellow.
     

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