Prototype-Based Contour Detection Applied to Segmentation of Phytoplankton Images
2013 (English)In: AWERProcedia Information Technology and Computer Science: 3rd World Conference on Information Technology (WCIT-2012) / [ed] Hafize Keser and Meltem Hakiz, 2013, 1285-1292 p.Conference paper (Refereed)
Novel prototype-based framework for image segmentation is introduced and successfully applied for cell segmentation in microscopy imagery. This study is concerned with precise contour detection for objects representing the Prorocentrum minimum species in phytoplankton images. The framework requires a single object with the ground truth contour as a prototype to perform detection of the contour for the remaining objects. The level set method is chosen as a segmentation algorithm and its parameters are tuned by differential evolution. The fitness function is based on the distance between pixels near contour in the prototype image and pixels near detected contour in the target image. Pixels “of interest correspond to several concentric bands of various width in outer and inner areas, relative to the contour. Usefulness of the introduced approach was demonstrated by comparing it to the basic level set and advanced Weka segmentation techniques. Solving the parameter selection problem of the level set algorithm considerably improved segmentation accuracy.
Place, publisher, year, edition, pages
2013. 1285-1292 p.
, AWERProcedia, ISSN 1247-5105 ; 3
Contour detection, level set, trainable segmentation, differential evolution, Quadratic-Chi distance
IdentifiersURN: urn:nbn:se:hh:diva-23643OAI: oai:DiVA.org:hh-23643DiVA: diva2:650739
3rd World Conference on Information Technology (WCIT-2012), 14-16 November 2012, University of Barcelon, Barcelona, Spain