计算机科学
分类
人工智能
分割
分类器(UML)
图像分割
模式识别(心理学)
膨胀(度量空间)
上下文图像分类
图像(数学)
计算机视觉
情报检索
数学
组合数学
作者
Gennaro Percannella,Paolo Soda,Mario Vento
标识
DOI:10.1109/cbms.2012.6266311
摘要
In this paper we propose a new method for cells segmentation in HEp-2 images addressing and overcoming the main limitations of the existing approaches. The proposed method adopts image reconstruction for a preliminary image segmentation and, then, it employs a sort of classifier-controlled dilation for better determining the structure of the cells, where the classifier is trained using data of the image at hand. We compare the performance of the proposed method with the most representative approaches from the scientific literature on a common and publicly available dataset of HEp-2 images.
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