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Video Processing Algorithm in Automated Semen Analysis using Optical Flow
Mutia F.a, Zakaria H.a
a Program Studi Teknik Elektro, Sekolah Teknik Elektro Dan Informatika, Institut Teknologi Bandung, Bandung, Jawa Barat, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 IEEE.Semen analysis is extensively practiced in laboratories for preparing cattle artificial insemination. Despite the fact that the laboratory analysis process is reliable, its complexity hinders the application of semen quality checking done by inseminators at the farms. Therefore, this research was conducted to create an algorithm that enables cattle semen analysis to be done easily and automatically at the farms. The algorithm uses the thresholding method to perform sperm detection and optical flow technique to calculate the velocity of each sperm. It has been successfully implemented on an Android application on Samsung S6 integrated with MooAnalyzer device. By comparing the system’s test results with Balai Inseminasi Buatan Lembang laboratory test standard, the system could calculate motile sperm concentration with an error of ± 8.53%, and a measurement variance of ± 2.95%. The entire calculation process took less than 30 seconds.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Android applications,Artificial insemination,Laboratory analysis,Optical flow techniques,Thresholding,Thresholding methods,Video processing,Video-processing algorithms[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]algorithm,Android application,motile sperm concentration,optical flow,thresholding,video processing[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ISESD.2019.8909593[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]