Publication: An Automatic Detection for Avian Blood Cell based on Adaptive Thresholding Algorithm
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Issued Date
2019
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-85080046565
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
BMEiCON 2019 - 12th Biomedical Engineering International Conference.
Suggested Citation
Meechart K., Auethavekiat S., Sa-Ing V. An Automatic Detection for Avian Blood Cell based on Adaptive Thresholding Algorithm. BMEiCON 2019 - 12th Biomedical Engineering International Conference.. doi:10.1109/BMEiCON47515.2019.8990182 Retrieved from: https://hdl.handle.net/20.500.14740/5096
Author(s)
Abstract
The chicken industry ranks tenth in the world in term of output in the world meat market. Red blood cell (RBC) count is one of the basic health screening protocol required in an exported meat industry. However, the human's automated blood analyzer cannot be applied to avian RBC, because the shape of avian blood (ellipse) is different from the mammal one (circle). In this paper, we propose 2-stage thresholding technique for automatic avian RBC counting. First, the blood smear slide is binarized into RBC and non-RBC area by applying Otsu thresholding. Then, image morphology and Otsu thresholding are reapplied to detect the blood nucleus. After that, the connected component analysis is applied to count the number of RBC. The experiment demonstrated that the proposed technique was simple and provided the count with error rate (2.23%) much less than the clinically acceptable value (5%). © 2019 IEEE.