Classification-Based Segmentation of the Region of Interest in Chromatographic Images

• Type: Article in International Conference Proceedings Book
• Date: 2011

Authors

Antonio V Sousa (Author) Other; Ana Maria Mendonca (Author) FEUP; Clara C Sa Miranda (Author) Other; Aurelio Campilho (Author) FEUP

Conference proceedings International

Title: Image Analysis and Recognition

Pages: 68-78

8th International Conference, ICIAR 2011

Burnaby, BC, Canada, June 22-24, 2011

Indexing

ISI Proceedings

ISI Web of Knowledge - 2 Citations

Scopus - 3 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-002-WYR

DOI: 10.1007/978-3-642-21596-4_8

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11