Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICIP.2004.1418708
Title: Segmentation of microscope cell images via adaptive eigenfilters
Authors: Kumar, S. 
Ong, S.H. 
Ranganath, S. 
Chew, F.T. 
Ong, T.C. 
Issue Date: 2004
Source: Kumar, S.,Ong, S.H.,Ranganath, S.,Chew, F.T.,Ong, T.C. (2004). Segmentation of microscope cell images via adaptive eigenfilters. Proceedings - International Conference on Image Processing, ICIP 1 : 135-138. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2004.1418708
Abstract: This paper presents the use of a PCA based approach to segment cells from RGB light microscope images. The proposed segmentation is accurate and robust under uneven illumination, lighting variation and noise. Principal component analysis (PCA) is first applied to the RGB color bands of the image. The image corresponding to the principal component has significantly better contrast over the original image. A set of eigenfilters is then obtained by applying PCA to local neighborhoods of this image. A pair of filters from this set, corresponding to the second and third largest eigenvalues, resembles ramp edge filters with orientations that adapt to the image. These edge filters are used to obtain the edgemap of the image. We define a criterion that enables accurate detection of valid edges of cells while suppressing noise. ©2004 IEEE.
Source Title: Proceedings - International Conference on Image Processing, ICIP
URI: http://scholarbank.nus.edu.sg/handle/10635/71726
ISBN: 0780385543
ISSN: 15224880
DOI: 10.1109/ICIP.2004.1418708
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