Modified Background Subtraction Statistic Models for Improvement Detection and Counting of Active Spermatozoa Motility

Masdiayasa, I G. Susrama and Wisana, I Dewa Gede Hari and Purnama, I K. Eddy and Purnomo, M. Hery (2018) Modified Background Subtraction Statistic Models for Improvement Detection and Counting of Active Spermatozoa Motility. LONTAR KOMPUTER, 9 (1). pp. 28-39. ISSN 2541-5832

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Abstract

An important early stage in the research of sperm analysis is the phase of sperm detection or separating sperm objects from images/video obtained from observations on semen. The success rate in separating sperm objects from semen fluids has an important role for further analysis of sperm objects. Algorithm or Background subtraction method is a process that can be used to separate moving objects (foreground) and background on sperm video data that tend to uni-modal. In this research, some of the subproject model statistics of substrata model are Gaussian single, Gaussian Mixture Model (GMM), Kernel Density Estimation and compared with some basic subtraction model background algorithm in detecting and counting the number of active spermatozoa. From the results of the tests, the Grimson GMM method has an fmeasure value of 0.8265 and succeeded in extracting the sperm form near its original form compared to other methods.

Item Type:	Article
Uncontrolled Keywords:	Spermatozoa, Background Subtraction, Motility, Statistic Model
Subjects:	R Medicine > Medical Electronics > Biomedical Engineering R Medicine > Medical Electronics > Clinical Engineering R Medicine > Medical Electronics
Divisions:	Poltekkes Kemenkes Surabaya > Pusat Penelitan dan Pengabdian Masyarakat > Pubikasi
Depositing User:	Nanik Indra Putri Sari
Date Deposited:	24 Aug 2021 01:31
Last Modified:	24 Aug 2021 02:12
URI:	http://repo.poltekkesdepkes-sby.ac.id/id/eprint/2441

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