A comparative study on feature selection for retinal vessel segmentation using FABC

Carmen Alina Lupascu, Domenico Tegolo, Emanuele Trucco

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    18 Citations (Scopus)

    Abstract

    This paper presents a comparative study on five feature selection heuristics applied to a retinal image database called DRIVE. Features are chosen from a feature vector (encoding local information, but as well information from structures and shapes available in the image) constructed for each pixel in the field of view (FOV) of the image. After selecting the most discriminatory features, an AdaBoost classifier is applied for training. The results of classifications are used to compare the effectiveness of the five feature selection methods.

    Original languageEnglish
    Title of host publicationComputer Analysis of Images and Patterns, Proceedings
    Subtitle of host publication13th International Conference, CAIP 2009, Münster, Germany, September 2-4, 2009. Proceedings
    EditorsXiaoyi Jiang, Nicolai Petkov
    Place of PublicationBerlin
    PublisherSpringer
    Pages655-662
    Number of pages8
    ISBN (Print)9783642037665
    DOIs
    Publication statusPublished - 2009
    Event13th International Conference on Computer Analysis of Images and Patterns - Munster, Germany
    Duration: 2 Sep 20094 Sep 2009
    http://cvpr.uni-muenster.de/CAIP2009/index.html

    Publication series

    NameLecture notes in computer science
    PublisherSpringer
    Volume5702

    Conference

    Conference13th International Conference on Computer Analysis of Images and Patterns
    Abbreviated titleCAIP 2009
    CountryGermany
    CityMunster
    Period2/09/094/09/09
    Internet address

    Keywords

    • Retinal images
    • vessel segmentation
    • AdaBoost classifier
    • feature selection
    • BLOOD-VESSELS
    • MATCHED-FILTERS
    • IMAGES
    • CLASSIFICATION

    Cite this

    Lupascu, C. A., Tegolo, D., & Trucco, E. (2009). A comparative study on feature selection for retinal vessel segmentation using FABC. In X. Jiang, & N. Petkov (Eds.), Computer Analysis of Images and Patterns, Proceedings: 13th International Conference, CAIP 2009, Münster, Germany, September 2-4, 2009. Proceedings (pp. 655-662). (Lecture notes in computer science; Vol. 5702). Springer . https://doi.org/10.1007/978-3-642-03767-2_80