Edge detection and filtering approach dedicated to microstructure images analysis

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Edge detection and filtering approach dedicated to microstructure images analysis

Łukasz Rauch, Jan Kusiak

AGH University of Science and Technology, Mickiewicza 30, 30-059 Kraków, Poland.

DOI:

https://doi.org/10.7494/cmms.2007.2.0160

Abstract:

The processing of microstructure images dedicated to detection of the borders between material grains is still a difficult task. It is basically caused by a superimposed noise in form of visible scratches and micro inclusions. Thus, the analysis of the microstructure photographs is performed manually in most cases, which is time consuming for numerous set of images. To avoid this problem the approach of automated images processing has been proposed. This approach consists of two parts i.e. edge detection, designed and implemented using Canny Detector method (Ritter & Wilson, 1996) and data filtering, based on Particle Dynamics method (Rauch & Kusiak, 2005a). The results obtained from this approach is in form of new microstructure image with smoothed grain areas and precisely detected grain borders. Such effect allows to optimize further analysis of material structure including e.g. Watershed (Haris et al., 1998) edge fulfilment or statistical calculations of average grain size. The paper presents basic assumptions of proposed approach and details of both algorithms. The results of the analysis of microstructure images using edge detection and filtering algorithms are presented.

Cite as:

Rauch, Ł., & Kusiak, J. (2007). Edge detection and filtering approach dedicated to microstructure images analysis. Computer Methods in Materials Science, 7(2), 305 – 310. https://doi.org/10.7494/cmms.2007.2.0160

Article (PDF):

Keywords:

Images analysis, Material microstructure, Grain analysis, Data filtering

References:

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