Institute of Information Theory and Automation

Publication details

Performance evaluation of image segmentation algorithms on microscopic image data

Journal Article

Beneš Miroslav, Zitová Barbara


serial: Journal of Microscopy vol.275, 1 (2015), p. 65-85

project(s): GAP103/12/2211, GA ČR

keywords: image segmentation, performance evaluation, microscopic images

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abstract (eng):

In our paper, we present a performance evaluation of image segmentation algorithms on microscopic image data. In spite of the existence of many algorithms for image data partitioning, there is no universal and "the best" method yet. Moreover, images of microscopic samples can be of various character and quality which can negatively influence the performance of image segmentation algorithms. Thus the issue of selecting suitable method for a given set of image data is of big interest. We carried out a large number of experiments with a variety of segmentation methods to evaluate the behavior of individual approaches on the testing set of microscopic images (cross-section images taken in three different modalities from the field of art restoration). The segmentation results were assessed by several indices used for measuring the output quality of image segmentation algorithms.

RIV: JC

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Institute of Information Theory and Automation