Classification-based segmentation of the region of interest in chromatographic images

  • Authors:

  • António V. Sousa;Ana Maria Mendonça;M. Clara Sá-Miranda;Aurélio Campilho

  • Affiliations:

  • Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal and Instituto Superior de Engenharia do Porto, Instituto Politécnico do Porto, Porto, Portugal;Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal and Faculdade de Engenharia, Universidade do Porto, Porto, Portugal;Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal and Instituto de Biologia Molecular e Celular, Porto, Portugal;Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal and Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

  • Venue:
  • ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
  • Year:
  • 2011

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Abstract

This paper proposes a classification-based method for automating the segmentation of the region of interest (ROI) in digital images of chromatographic plates. Image segmentation is performed in two phases. In the first phase an unsupervised learning method classifies the image pixels into three classes: frame, ROI or unknown. In the second phase, distance features calculated for the members of the three classes are used for deciding on the new label, ROI or frame, for each individual connected segment previously classified as unknown.The segmentation result is post-processed using a sequence of morphological operators beforeobtaining the final ROI rectangular area. The proposed methodology, which is the initial step for the development of a screening tool for Fabry disease, was successfully evaluated in a dataset of 58 chromatographic images.