Mixture gaussian V2 based microscopic movement detection of human spermatozoa

International Journal of Advances in Intelligent Informatics

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Field Value
 
Title Mixture gaussian V2 based microscopic movement detection of human spermatozoa
 
Creator Setiawan, Ariyono
Diyasa, I Gede Susrama Mas
Hatta, Moch
Puspaningrum, Eva Yulia
 
Subject Microscopic video; Mixture of Gaussian V2;Movement detection; Spermatozoa
 
Description Healthy and superior sperm is the main requirement for a woman to get pregnant. To find out how the quality of sperm is needed several checks. One of them is a sperm analysis test to see the movement of sperm objects, the analysis is observed using a microscope and calculated manually. The first step in analyzing the scheme is detecting and separating sperm objects. This research is detecting and calculating sperm movements in video data. To detect moving sperm, the background processing of sperm video data is essential for the success of the next process. This research aims to apply and compare some background subtraction algorithms to detect and count moving sperm in microscopic videos of sperm fluid, so we get a background subtraction algorithm that is suitable for the case of sperm detection and sperm count. The research methodology begins with the acquisition of sperm video data. Then, preprocessing using a Gaussian filter, background subtraction, morphological operations that produce foreground masks, and compared with moving sperm ground truth images for validation of the detection results of each background subtraction algorithm. It also shows that the system has been able to detect and count moving sperm. The test results show that the MoG (Mixture of Gaussian) V2 (2 Dimension Variable) algorithm has an f-measure value of 0.9449 and has succeeded in extracting sperm shape close to its original form and is superior compared to other methods. To conclude, the sperm analysis process can be done automatically and efficiently in terms of time.
 
Publisher Universitas Ahmad Dahlan
 
Contributor
 
Date 2020-07-12
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/507
10.26555/ijain.v6i2.507
 
Source International Journal of Advances in Intelligent Informatics; Vol 6, No 2 (2020): July 2020; 210-222
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/507/ijain_v6i2_p201-222
 
Rights https://creativecommons.org/licenses/by-sa/4.0
 

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