Institute of Information Theory and Automation

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Digital Image Processing of Cross-section Samples

Miroslav Beneš
Defense type: 
Date of Event: 
budova ÚTIA AV ČR v.v.i., Pod Vodárenskou věží 4, Praha 8, místnost č. 103
The thesis is aimed on the digital analysis and processing of microscopic image data with a focus on cross-section samples from the artworks which fall into cultural heritage domain. It contributes to solution of two different problems of image processing – image segmentation and image retrieval. The performance evaluation of different image segmentation methods on a data set of cross-section images is carried out in order to study the behavior of individual approaches and to propose guidelines how to choose suitable method for segmentation of microscopic images. Moreover, the benefit of segmentation combination approach is studied and several distinct combination schemes are proposed. The evaluation is backed up by a large number of experiments where image segmentation algorithms are assessed by several segmentation quality measures. Applicability of achieved results is shown on image data of different origin. In the second part, content-based image retrieval of cross-section samples is addressed and functional solution is presented. Its implementation is included in Nephele system, an expert system for processing and archiving the material research reports with image processing features, designed and implemented for the cultural heritage application area.
2018-05-03 08:01