Please use this identifier to cite or link to this item:
|Title:||Invariant texture classification for biomedical cell specimens via non-linear polar map filtering||Authors:||Kumar, S.
Support vector machine
|Issue Date:||Jan-2010||Citation:||Kumar, S., Ong, S.H., Ranganath, S., Chew, F.T. (2010-01). Invariant texture classification for biomedical cell specimens via non-linear polar map filtering. Computer Vision and Image Understanding 114 (1) : 44-53. ScholarBank@NUS Repository. https://doi.org/10.1016/j.cviu.2009.08.005||Abstract:||A novel texture-based classification scheme for cell specimens that is robust over a range of orientation, scale and contrast values is proposed. We achieve this robustness by first segmenting the cell specimens and for each specimen, we find the largest ellipse that can be contained within it, and from this, we then construct an orientation and scale-invariant polar map. Non-linear filtering by normalized cross-correlation is then performed on the polar map to obtain contrast-invariant similarity maps. Local and global energy measures are finally extracted from these maps and classified using a support vector machine. Experimental results show that the proposed method achieves an average accuracy of about 97% in classifying six species of pollen, fungal and fern spores. In addition, every invariant property was validated through a series of experiments. Unlike conventional wavelet decomposition, Laws filtering and co-occurrence methods, our method shows a consistently high classification accuracy for all classes of cell specimens in an airspora dataset. © 2009 Elsevier Inc. All rights reserved.||Source Title:||Computer Vision and Image Understanding||URI:||http://scholarbank.nus.edu.sg/handle/10635/50958||ISSN:||10773142||DOI:||10.1016/j.cviu.2009.08.005|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.