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Automatic Lane and Band Detection in Images of Thin Layer Chromatography

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Image Analysis and Recognition (ICIAR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3212))

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Abstract

This work aims at developing an automatic method for the analysis of TLC images for measuring a set of features that can be used for the characterization of the distinctive patterns that result from the separation of oligosaccharides contained in human urine. This paper describes the methods developed for the automatic detection of the lanes contained in TLC images, and for the automatic separation of bands for each detected lane. The extraction of quantitative information related with each band was accomplished with two methods: the EM expectation-maximization and nonlinear least squares trust-region algorithms. The results of these methods, as well as additional quantitative information related with each band, are also presented.

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© 2004 Springer-Verlag Berlin Heidelberg

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Sousa, A.V., Aguiar, R., Mendonça, A.M., Campilho, A. (2004). Automatic Lane and Band Detection in Images of Thin Layer Chromatography. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_20

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  • DOI: https://doi.org/10.1007/978-3-540-30126-4_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23240-7

  • Online ISBN: 978-3-540-30126-4

  • eBook Packages: Springer Book Archive

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