Research on Biological Materials by Applied Technology with an Algorithm for Identifying and Counting Cells in Microscopic Particle Image

Abstract:

Cells are fundamental units of life, and the key point in the field of biomaterial. Biological cells are always with high density, small nucleus and much impurities. Based on the technology of image processing, we propose a new method to count cells on the image of microscopic cells with high level of recognition. To precisely count the number, our method includes edge detecting and marking, efficient usage of three channel information of enhanced nucleus, binaryzation of dynamic threshold in separated areas and finally denoising. The experiment shows that the method is precise and quickly-reacted, moreover it can effectively rule out the impact of impurities. With little adjustment, it can apply to some other fields, not only decrease the labor involved, but the budget as well.

• Periodical: Applied Mechanics and Materials (Volume 540)
• Pages: 352-355
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.540.352
• Online since: April 2014
• Authors: Sui Yuan Zhang*, Rui Wang, Xian Qiao Chen, Ze Wu Jiang, Xiang Cai
• Keywords: Biological Materials, Cell Microscopic Images, Counting Cells, Image Edge Detection, Particle Identification

References

[1] Zhao Xin Xin. Counting method in the images of biological tissue. Huazhong University of Science and Technology, (2012).

[2] Zhong Cai. The technique research of blood cells in the microscopic images of urine. East China Normal University, (2008).

[3] Yang Kun, Zeng Li Bo, Wang Dian Cheng, the quick algorithm of expanding and eroding operation in mathematical morphology . Computer engineering and application, 2006, 41(34): 54-56.

[4] Lin Kai Yan, Wu Jun Bo, Xu Li Hong. The summation on the method of splitting of colored images. Journals of images and graphics, 2005, 10(1): 1-10.

[5] Qi LI Na, Zhang Bo, Wang Zhan Kai. The application of maximum classes error in the process of images. Radio engineering, 2006, 36(7): 25-26.

[6] Yang Kun, Zeng Li Bo, Wang Dian Cheng, the quick algorithm of expanding and eroding operation in mathematical morphology . Computer engineering and application, 2006, 41(34): 54-56.

[7] Lei Yan Ming, Huang Qiu Yuan. The edge detection of images based on mathematical morphology. Journal of Wuhan University of Technology: Information and Management Engineering Edition, 2005, 27(5): 25-27.

[8] Xun Zheng Guang, Bao Dong Lai, Zhang Li Xin. The marking algorithm of adjoining regions on binary images based on recursion. Computer Engineering, 2006, 32(24): 186-188.

[9] Laganière R. OpenCV 2 computer vision application programming cookbook. Packt Publishing, (2011).