Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

This is an Open Access publication published under CSC-OpenAccess Policy.
Fast Segmentation of Sub-cellular Organelles
Dilip Kumar Prasad, Chai Quek, Maylor K. H. Leung
Pages - 317 - 325     |    Revised - 15-09-2012     |    Published - 24-10-2012
Volume - 6   Issue - 5    |    Publication Date - October 2012  Table of Contents
Segmentation, Bio-cell Organelles, Fluorescence Microscopy, Ellipse Detection
Segmentation and counting sub-cellular structure is a very challenging problem even for medical experts. A fast and efficient method for segmentation and counting of sub-cellular structure is proposed. The proposed method uses a hybrid combination of several image processing techniques and is effective in segmenting the sub-cellular structures in a fast and effective manner.
CITED BY (6)  
1 Niri, E. D., & Singh, T. (2016). Unscented Transformation based estimation of parameters of nonlinear models using heteroscedastic data. Pattern Recognition, 55, 160-171.
2 Prasad, D. K., & Quek, C. (2013, December). Comparison of error bounds for non-parametric dominant point detection. In Information, Communications and Signal Processing (ICICS) 2013 9th International Conference on (pp. 1-5). IEEE.
3 Prasad, D. K. (2013). Object detection in real images. arXiv preprint arXiv:1302.5189.
4 Prasad, D. K. (2013). Geometric primitive feature extraction-concepts, algorithms, and applications. arXiv preprint arXiv:1305.3885.
5 Prasad, D. K. (2012). Survey of the problem of object detection in real images. International Journal of Image Processing (IJIP), 6(6), 441.
6 Prasad, D. K. (2012). Assessing error bound for dominant point detection. International Journal of Image Processing (IJIP), 6(5), 326.
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PdfSR
1 S. Kumar, S. H. Ong, S. Ranganath, and F. T. Chew, "Invariant texture classification for biomedical cell specimens via non-linear polar map filtering," Computer Vision and Image Understanding, vol. 114, pp. 44-53, Jan 2010.
2 G. Dong, N. Ray, and S. T. Acton, "Intravital leukocyte detection using the gradient inverse coefficient of variation," IEEE Transactions on Medical Imaging, vol. 24, pp. 910-924, 2005.
3 X. Z. Bai, C. M. Sun, and F. G. Zhou, "Splitting touching cells based on concave points and ellipse fitting," Pattern Recognition, vol. 42, pp. 2434-2446, Nov 2009.
4 T. Peng, G. M. C. Bonamy, E. Glory-Afshar, D. R. Rines, S. K. Chanda, and R. F. Murphy,"Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns," Proceedings of the National Academy of Sciences of the USA, vol. 107, pp. 2944-2949, Feb 2010.
5 D. K. Prasad, M. K. H. Leung, C. Quek, and S.-Y. Cho, "A novel framework for making dominant point detection methods non-parametric," Image and Vision Computing, 2012.
6 D. K. Prasad and M. K. H. Leung, "Reliability/Precision Uncertainty in Shape Fitting Problems," in IEEE International Conference on Image Processing, Hong Kong, 2010, pp.4277-4280.
7 D. K. Prasad and M. K. H. Leung, "Polygonal representation of digital curves," in Digital Image Processing, S. G. Stanciu, Ed., ed: InTech, 2012, pp. 71-90.
8 D. K. Prasad, C. Quek, and M. K. Leung, "A non-heuristic dominant point detection based on suppression of break points," in Image Analysis and Recognition. vol. 7324, A.Campilho and M. Kamel, Eds., ed Aveiro, Portugal: Springer Berlin Heidelberg, 2012, pp.269-276.
9 D. K. Prasad, C. Quek, M. K. H. Leung, and S. Y. Cho, "A parameter independent line fitting method," in Asian Conference on Pattern Recognition (ACPR), Beijing, China, 2011,pp. 441-445.
10 D. K. Prasad, "Assessing error bound for dominant point detection," International Journal of Image Processing, vol. 6, 2012.
11 N. Barnes, G. Loy, and D. Shaw, "The regular polygon detector," Pattern Recognition, vol.43, pp. 592-602, 2010.
12 A. Carmona-Poyato, R. Medina-Carnicer, F. J. Madrid-Cuevas, R. Muoz-Salinas, and N. L.Fernndez-Garca, "A new measurement for assessing polygonal approximation of curves,"Pattern Recognition, vol. 44, pp. 45-54, 2011.
13 P. C. Chung, C. T. Tsai, E. L. Chen, and Y. N. Sun, "Polygonal approximation using a competitive Hopfield neural network," Pattern Recognition, vol. 27, pp. 1505-1512, 1994.
14 T. M. Cronin, "A boundary concavity code to support dominant point detection," Pattern Recognition Letters, vol. 20, pp. 617-634, 1999.
15 F. Feschet, "Canonical representations of discrete curves," Pattern Analysis and Applications, vol. 8, pp. 84-94, 2005.
16 D. K. Prasad, M. K. H. Leung, and S. Y. Cho, "Edge curvature and convexity based ellipse detection method," Pattern Recognition, vol. 45, pp. 3204-3221, 2012.
17 D. K. Prasad and M. K. H. Leung, "An ellipse detection method for real images," in 25th International Conference of Image and Vision Computing New Zealand (IVCNZ 2010),Queenstown, New Zealand, 2010, pp. 1-8.
18 D. K. Prasad and M. K. H. Leung, "Methods for ellipse detection from edge maps of real images," in Machine Vision - Applications and Systems, F. Solari, M. Chessa, and S.Sabatini, Eds., ed: InTech, 2012, pp. 135-162.
19 X. Bai, C. Sun, and F. Zhou, "Splitting touching cells based on concave points and ellipse fitting," Pattern Recognition, vol. 42, pp. 2434-2446, 2009.
20 D. K. Prasad, "Adaptive traffic signal control system with cloud computing based online learning," in 8th International Conference on Information, Communications, and Signal Processing (ICICS 2011), Singapore, 2011.
21 G. Heitz, G. Elidan, B. Packer, and D. Koller, "Shape-based object localization for descriptive classification," International Journal of Computer Vision, vol. 84, pp. 40-62,2009.
22 D. K. Prasad and M. K. H. Leung, "Error analysis of geometric ellipse detection methods due to quantization," in Fourth Pacific-Rim Symposium on Image and Video Technology (PSIVT 2010), Singapore, 2010, pp. 58 - 63.
23 D. K. Prasad, M. K. H. Leung, and C. Quek, "DEB: Definite error bounded tangent estimator for digital curves," Image and Vision Computing, 2012(under review).
24 D. K. Prasad, R. K. Gupta, and M. K. H. Leung, "An Error Bounded Tangent Estimator for Digitized Elliptic Curves," in Discrete Geometry for Computer Imagery. vol. 6607, ed:Springer Berlin / Heidelberg, 2011, pp. 272-283.
25 I. M. Anderson and J. C. Bezdek, "Curvature and tangential deflection of discrete arcs: a theory based on the commutator of scatter matrix pairs and its application to vertex detection in planar shape data," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-6, pp. 27-40, 1984.
26 D. M. Tsai and M. F. Chen, "Curve fitting approach for tangent angle and curvature measurements," Pattern Recognition, vol. 27, pp. 699-711, 1994.
27 B. Dubuc and S. W. Zucker, "Complexity, confusion, and perceptual grouping. Part I: The curve-like representation," Journal of Mathematical Imaging and Vision, vol. 15, pp. 55-82,2001.
28 D. K. Prasad, C. Quek, and M. K. Leung, "A precise ellipse fitting method for noisy data," in Image Analysis and Recognition, A. Campilho and M. Kamel, Eds., ed Aveiro, Portugal:Springer Berlin Heidelberg, 2012, pp. 253-260.
29 D. Chaudhuri, "A simple least squares method for fitting of ellipses and circles depends on border points of a two-tone image and their 3-D extensions," Pattern Recognition Letters,vol. 31, pp. 818-829, Jul 2010.
30 M. Harker, P. O'Leary, and P. Zsombor-Murray, "Direct type-specific conic fitting and eigenvalue bias correction," Image and Vision Computing, vol. 26, pp. 372-381, 2008.
31 E. S. Maini, "Enhanced direct least square fitting of ellipses," International Journal of Pattern Recognition and Artificial Intelligence, vol. 20, pp. 939-953, 2006.
Mr. Dilip Kumar Prasad
- Singapore
Mr. Chai Quek
Nanyang Technological University - Singapore
Mr. Maylor K. H. Leung
Universiti Tunku Abdul Rahman - Malaysia