Lane Background Removal for the Classification of Thin-Layer Chromatography Images

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

Bruno Moreira (Author) FEUP; António Sousa (Author) FEUP; Ana Maria Mendonca (Author) FEUP; Aurelio Campilho (Author) FEUP

Conference proceedings International

Title: IMAGE ANALYSIS AND RECOGNITION

Pages: 556-564

10th International Conference on Image Analysis and Recognition (ICIAR)

Pvoa do Varzim, PORTUGAL, JUN 26-28, 2013

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Scientific classification

FOS: Natural sciences > Computer and information sciences

CORDIS: Technological sciences > Engineering

Other information

Authenticus ID: P-008-E9Y

DOI: 10.1007/978-3-642-39094-4_63

Abstract (EN): This paper describes a methodology to remove the background of the lanes in Thin Layer Chromatography (TLC) images, aiming at improving band detection and classification. The storage of the biological samples to be analyzed by TLC is usually done via plastic containers. Filter paper is an alternative that allows reduced costs and higher portability, but it increases the complexity of the image analysis stage due to lane background alteration. In order to overcome this problem, a negative control lane is included in every chromatographic plate. After image preprocessing and lane detection stages, a background profile is generated by processing the negative control lane using the Discrete Wavelet Transform (DWT). This profile is then subtracted to the profiles of all other sample lanes in order to overcome the data degradation introduced by filter paper usage. For assessing the proposed background removal process, 105 TLC lanes, with and without background, were used as input for three one-class classifiers. In all cases, the best results were achieved for the lanes after background removal.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9