title: Automatic lane segmentation in TLC images using the continuous wavelet transform.
abstract: This paper describes a new methodology for lane detection in Thin-Layer Chromatography images. An approach based on the continuous wavelet transform is used to enhance the relevant lane information contained in the intensity profile obtained from image data projection. Lane detection proceeds in three phases: the first obtains a set of candidate lanes, which are validated or removed in the second phase; in the third phase, lane limits are calculated, and subtle lanes are recovered. The superior performance of the new solution was confirmed by a comparison with three other methodologies previously described in the literature.
authors.affiliation: INEB-Instituto de Engenharia Biomédica, Campus da FEUP, Universidade do Porto, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal ; Faculdade de Engenharia da Universidade do Porto (FEUP), 4200-465 Porto, Portugal.
authors.forename: Bruno
authors.initials: B
authors.lastname: Moreira
authors.forename: António
authors.initials: A
authors.lastname: Sousa
authors.forename: Ana Maria
authors.initials: AM
authors.lastname: Mendonça
authors.forename: Aurélio
authors.initials: A
authors.lastname: Campilho
mesh_terms: D000465:Algorithms; D002855:Chromatography, Thin Layer / Q000706:statistics & numerical data*; D016208:Databases, Factual / Q000706:statistics & numerical data; D000795:Fabry Disease / Q000175:diagnosis / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008403:Mass Screening / Q000706:statistics & numerical data; D014281:Trihexosylceramides / Q000032:analysis; D058067:Wavelet Analysis
chemical_list: D014281:Trihexosylceramides; C018549:globotriaosylceramide