Pengukuran Badan Ikan Berupa Estimasi Panjang, Lebar, dan Tinggi Berdasarkan Visual Capture

  • Raihan Islamadina Universitas Serambi Mekkah
  • Nuriza Pramita Universitas Serambi Mekkah
  • Fitri Arnia Universitas Syiah Kuala
  • Khairul Munadi Universitas Syiah Kuala
  • TWK Muhammad Iqbal Universitas Syiah Kuala
Keywords: panjang ikan, lebar ikan, tinggi ikan, estimasi, pengukuran badan ikan, visual capture

Abstract

Currently, fish measurement process is done manually using the gauge which can cause inappropriate, ineffective result, and requires long time to finish, especially for a great amount of fish. Therefore, an automatic fish body measurement technique in the form of estimation of length, width, and height of fish based on visual capture is needed to facilitate fish body measurement to become more effective and efficient. This research uses five samples of fish in measuring length, width, and height manually to obtain the average data/value as the calibration of reference value for calculation process in the system and to be stored in the database. The stages begin with capturing fish image using a digital camera. Then, preprocessing stage was carried out to get the grayscale image of the fish. The object of the grayscale image was then segmented to separate the important and unimportant part of the object. Lastly, feature extraction process of the fish body from the calibration average value was carried out, and the estimated value of length, width, and height of fish are obtained automatically. The results show that the automatic measurement technique of fish body based on visual capture was able to produce the truth degree of accuracy of 80% to 95%.

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Published
2018-03-05
How to Cite
Raihan Islamadina, Nuriza Pramita, Fitri Arnia, Khairul Munadi, & TWK Muhammad Iqbal. (2018). Pengukuran Badan Ikan Berupa Estimasi Panjang, Lebar, dan Tinggi Berdasarkan Visual Capture. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 7(1), 57-63. Retrieved from https://dev.journal.ugm.ac.id/v3/JNTETI/article/view/2793
Section
Articles