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A Comparative Study on Feature Selection for Retinal Vessel Segmentation Using FABC

  • Conference paper
Computer Analysis of Images and Patterns (CAIP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5702))

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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.

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© 2009 Springer-Verlag Berlin Heidelberg

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Lupaşcu, C.A., Tegolo, D., Trucco, E. (2009). A Comparative Study on Feature Selection for Retinal Vessel Segmentation Using FABC. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_80

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  • DOI: https://doi.org/10.1007/978-3-642-03767-2_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03766-5

  • Online ISBN: 978-3-642-03767-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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