Author/Editor		Oyebode, Kazeem O.; Tapamo, Jules R.
Title		Adaptive parameter selection for graph cut-based segmentation on cell images
Type		članek
Vol. and No.		Letnik 35, št. 1
Publication year		2016
Volume		str. 29-37, V
ISSN		1580-3139 - Image Analysis & Stereology online journal (Printed version).
Language		eng
Abstract		Graph cut segmentation approach provides a platform for segmenting images in a globally optimised fashion. The graph cut energy function includes a parameter that adjusts its data term and smoothness term relative to each other. However, one of the key challenges in graph cut segmentation is finding a suitable parameter value that suits a given segmentation. A suitable parameter value is desirable in order to avoid image over- segmentation or under-segmentation. To address the problem of trial and error in manual parameter selection, we propose an intuitive and adaptive parameter selection for cell segmentation using graph cut. The greyscale image of the cell is logarithmically transformed to shrink the dynamic range of foreground pixels in order to extract the boundaries of cells. The extracted cell boundary dynamically adjusts and contextualises the parameter value of the graph cut, countering its shrink bias. Experiments suggest that the proposed model outperforms previous cell segmentation approaches.
Keywords		delitev celic razrez grafa izbira parametrov cell segmentation graph cut parameter selection