Abstract
In this paper we propose a novel approach to HEp-2 cell segmentation based on the framework of verification-based multithreshold probing. Cell hypotheses are generated by binarization using hypothetic thresholds and accepted/rejected by a verification procedure. The proposed method has the nice property of combining both adaptive local thresholding and involvement of high-level knowledge. We have realized a prototype implementation using a simple rule-based verification procedure. Experimental evaluation has been performed on two public databases. It is shown that our approach outperforms a number of existing methods.
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Jiang, X., Percannella, G., Vento, M. (2015). A Verification-Based Multithreshold Probing Approach to HEp-2 Cell Segmentation. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9257. Springer, Cham. https://doi.org/10.1007/978-3-319-23117-4_23
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DOI: https://doi.org/10.1007/978-3-319-23117-4_23
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