Abstract

Fish contains a lot of nutrients that are very beneficial for the body, but fish are often traded both live and dead. To observe the freshness of the fish, it is done by looking at the changes that occur in the fish's eyes and gills using UV imaging and image processing. Indicators of fish freshness quality can be seen through the color and smell. By using UV imaging can be seen the reaction that occurs in fish. Using UV light means freeing electrons from atoms or molecules, which can cause chemical reactions. After collecting data using UV imaging, the freshness level of the fish will be determined using deep learning. Deep learning is used to determine the level of segmentation of fish freshness. These results indicate that using DNN successfully assesses fish freshness non-destructively only by capturing fish images with UV light with a wavelength of 365-400 nm. By using segmentation based on RGB, CIE L∗a∗b, and HSV it is proven that this technique can accurately reveal changes in fish freshness with an R of 0.993. So that with this technique it is possible to evaluate the freshness level of fish non-destructively and classification of fish can be done online.

Original languageEnglish
Title of host publication2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages839-844
Number of pages6
ISBN (Electronic)9798350309225
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Lombok, Indonesia
Duration: 14 Nov 202315 Nov 2023

Publication series

Name2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Proceedings

Conference

Conference2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023
Country/TerritoryIndonesia
CityLombok
Period14/11/2315/11/23

Keywords

  • deep neural network
  • fish freshness
  • image processing
  • uv imaging

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