Processing of microscope
images in medicine is one of the priority research areas. At the same time, the
processing of images of cytological preparations occupies a special place. This
is due to the fact that such studies allow for a comprehensive diagnosis of the
state of human health, identify and prevent the development of diseases in the
early stages. But this requires the results of processing the original images,
which provide additional information. To do this, we investigate the
possibility of using wavelet analysis in color models RGB and HSV. We showed
the importance of using the HSV model for more information. It is shown that
the procedure for changing the contrast in the HSV model is better than the
contrast change procedure in the RGB model when using wavelet analysis.
Cite this paper
Lyashenko, V. V. , Babker, A. M. and Lyubchenko, V. A. (2017). Wavelet Analysis of Cytological Preparations Image in Different Color Systems. Open Access Library Journal, 4, e3760. doi: http://dx.doi.org/10.4236/oalib.1103760.
Hameed, B.M., Aboob, H.S.
and Musa, R.J. (2016) Immunohistochemical Expression of VEGF in Relation to
VEGFR and CD34 in NHL Using Digital Image Analysis System. Iraqi Journal of Hematology, 5, 19-31.
Myburgh,
H.C., van Zijl, W.H., Swanepoel, D., Hellstrom, S. and Laurent, C. (2016) Otitis Media Diagnosis for Developing Countries
Using Tympanic Membrane Image- Analysis. EBioMedicine,
5, 156-160. https://doi.org/10.1016/j.ebiom.2016.02.017
Singh,
S. and Gupta, R. (2012) Identification of Components of Fibroadenoma in Cytology
Preparations Using Texture Analysis: A Morphometric Study. Cytopathology,
23, 187-191. https://doi.org/10.1111/j.1365-2303.2011.00854.x
Mahendran,
G., Babu, R. and Sivakumar, D. (2014) Automatic Segmentation and Classification
of Pap Smear Cells. International Journal
of Management, IT and Engineering,
4, 100-108.
Saha, M., Agarwal, S., Arun, I.,
Ahmed, R., Chatterjee, S., Mitra, P. and Chakraborty, C. (2015) Histogram Based
Thresholding for Automated Nucleus Segmentation Using Breast Imprint Cytology.
In: Advancements of Medical
Electronics,
Springer India, 49-57. https://doi.org/10.1007/978-81-322-2256-9_5
Lyashenko,
V.V., Babker, A.M.A.A. and Kobylin,
O.A. (2016) The Methodology of Wavelet Analysis as a Tool for Cytology
Preparations Image Processing. Cukurova Medical Journal, 41, 453-463. https://doi.org/10.17826/cukmedj.237468
Kingsbury,
N. (1999) Image Processing with Complex Wavelets. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering
Sciences,357, 2543-2560. https://doi.org/10.1098/rsta.1999.0447
Kobylin,
O. and Lyashenko, V. (2014) Comparison of Standard Image Edge Detection
Techniques and of Method Based on Wavelet Transform. International Journal of Advanced Research, 2, 572-580.
Lyashenko, V., Matarneh, R., Kobylin, O. and Putyatin, Y.
(2016) Contour Detection and Allocation for Cytological Images Using Wavelet
Analysis Methodology. International
Journal of Advance Research in Computer Science and Management Studies, 4,
85-94.
Lyashenko,
V.V., Babker, A.M.A.A. and Kobylin, O.A. (2016) Using the Methodology of Wavelet
Analysis for Processing Images of Cytology Preparations. National Journal of Medical Research, 6, 98-102.
Lyashenko, V., Matarneh, R. and Kobylin, O. (2016)
Contrast Modification as a Tool to Study the Structure of Blood Components. Journal
of Environmental Science, Computer
Science and Engineering & Technology, 5, 150-160.
Dey, N., Ashour, A.S.,
Ashour, A.S. and Singh, A. (2015) Digital Analysis of Microscopic Images in Medicine. Journal of Advanced Microscopy Research, 10, 1-13. https://doi.org/10.1166/jamr.2015.1229
Cheng,
H.D., Jiang, X.H., Sun, Y. and Wang, J. (2001) Color Image Segmentation: Advances
and Prospects. Pattern Recognition, 34, 2259-2281. https://doi.org/10.1016/S0031-3203(00)00149-7
Comaniciu,
D. and Meer, P. (1997) Robust Analysis of Feature Spaces: Color Image Segmentation.
Proceedingsof IEEE
Computer Society Conference on Computer Vision and Pattern Recognition, Santa Barbara, 17-19
June 1997, 750-755. https://doi.org/10.1109/cvpr.1997.609410
Chen,
W., Shi, Y.Q. and Xuan, G. (2007) Identifying Computer Graphics Using HSV Color
Model and Statistical Moments of Characteristic Functions. IEEE International Conference on Multimedia and Expo, Beijing, 2-5 July 2007, 1123-1126. https://doi.org/10.1109/icme.2007.4284852
