Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Determination and Classification of Blood Types using Image Processing Techniques

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
G. Ravindran, T. Joby Titus, M. Pravin, P. Pandiyan
10.5120/ijca2017912592

G Ravindran, Joby T Titus, M Pravin and P Pandiyan. Determination and Classification of Blood Types using Image Processing Techniques. International Journal of Computer Applications 157(1):12-16, January 2017. BibTeX

@article{10.5120/ijca2017912592,
	author = {G. Ravindran and T. Joby Titus and M. Pravin and P. Pandiyan},
	title = {Determination and Classification of Blood Types using Image Processing Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2017},
	volume = {157},
	number = {1},
	month = {Jan},
	year = {2017},
	issn = {0975-8887},
	pages = {12-16},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume157/number1/26794-2016912592},
	doi = {10.5120/ijca2017912592},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Determining of blood types is very important during emergency situation before administering a blood transfusion. Presently, these tests are performed manually by technicians, which can lead to human errors. Determination of the blood types in a short period of time and without human errors is very much essential. A method is developed based on processing of images acquired during the slide test. The image processing techniques such as thresholding and morphological operations are used. The images of the slide test are obtained from the pathological laboratory are processed and the occurrence of agglutination are evaluated. Thus the developed automated method determines the blood type using image processing techniques. The developed method is useful in emergency situation to determine the blood group without human error.

References

  1. Neha Srivathsa; Dhananjaya Dendukuri, “Automated ABO Rh-D blood type detection using smartphone imaging for point-of-care medical diagnostics” IEEE Conference Publications, Year: 2016, Pages: 4345 – 4348.
  2. Fabien Picot; Julien Pichette, "Imaging system based on diffusive reflectance spectroscopy for bloodvessels detection during brain biopsy procedure” IEEE Conference Publications,Year: 2016, Pages: 1 – 1
  3. Tejaswini.H.V, M.S. Mallikarjuna Swamy, “Determination and classification of blood types using image processing techniques” ITSI Transactions on Electrical and Electronics Engineering (ITSI-TEEE)”, Volume-2, Issue-2-2014, pp.29-33.
  4. Ana Ferraz, Filomena Soares “A Prototype for Blood Typing Based on Image Processing” The Fourth International Conference on Sensor Device Technologies and Applications, Copyright (c) IARIA, 2013.
  5. Miss Hetal J.Vala, Prof.Astha Baxi “A Review on Otsu Image Segmentation Algorithm” Volume 2, Issue 2, February 2013.
  6. Miss.Madhuri, G.Bhamare “Automatic Blood cell Analysis by using Digital Image processing:A preliminary study”, Vol-2, Issue-9, September-2013.
  7. T.Romen Singh, Sudipta Roy, O.Imocha Singh, Tejmani Sinam and Kh.Manglem Singh “A New Local Adaptive Thresholding Technique in Binarization”, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 6, No 2, November 2011.
  8. Er.Nirpjeet kaur, Er.Rajpreet kaur, “A review on various methods of Image thresholding”, Er.Nirpjeet kaur et al. / International Journal on Computer Science and Engineering (IJCSE), Vol. 3 No. 10 October 2011.
  9. Qingqiang Yang, Wenxiong Kang “General Research on Image Segmentation algorithms”, I.J. Image, Graphics and Signal Processing, 2009, P.No:1-8.
  10. Khurram Khurshid, Imran Siddiqi, Claudie Faure, Nicole Vincent “Comparison of Niblack inspired Binarization methods for ancient documents” DDR, Volume 7247 of SPIE, Page 1-10.
  11. M.R.Brown, P.Crim, “Organizing the antibody identification process” Clin Lab Sci, Vol.20, 2007, Pp.122-126.

Keywords

Blood samples; morphological techniques; Luminance; quantification..