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Palm Oil Fresh Fruit Bunch Grading System Using Multispectral Image Analysis in HSV
Setiawan A.W.a, Prasetya O.E.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, 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]© 2020 IEEE.Even though Indonesia is the largest palm oil producer in the world, but the productivity is very low compared to other countries. The main research question is how to increase productivity. In general, there are three ripeness criteria that are used in Indonesia, i.e. unripe; ripe; and overripe. Several studies have been done to improve the grading system. The common method that can be used to assess the maturity level of FFB is using a standard image processing technique. Using this image-based assessment, several parameters can be obtained in more detail, such as color; texture; and the number of fruitlets that are detached from the FFB. Further research states that the FFB image can be observed at several different wavelengths. This study will focus on productivity improvement in the palm oil mill through the development of an objective Fresh Fruit Bunch (FFB) grading system. In this study, the multispectral image-based is introduced to assess the level of FFB’s ripeness. There are 19 LEDs with different wavelengths that are used as source light, i.e. 615 nm, 635 nm, 615 nm, 660 nm, 680 nm, 710 nm, 730 nm, 750 nm, 765 nm, 780 nm, 810 nm, 830 nm, 850 nm, 870 nm, 890 nm, 910 nm, 940 nm, module 780 nm, module and LED 780 nm. Using these different source lights, the FFB is captured using a camera to obtain the RGB image of the FFB. In this research, HSV color space is introduced to assess the maturity level of FFB. One of the main contributions of this study is that the 940 nm wavelength gives the best result for determining the maturity level of FFB.[/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]Grading system,HSV color spaces,Maturity levels,Multi-spectral image analysis,Multispectral images,Productivity improvements,Research questions,Standard images[/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]HSV,multispectral image,palm oil FFB,ripeness grading[/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/ICIoT48696.2020.9089431[/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]