An automated vision system for measurement of zebrafish length using low-cost orthogonal web cameras

Al-Jubouri, Qussay; Al-Nuaimy, Waleed; Al-Taee, Majid A.; Young, Iain S.

doi:10.1016/j.aquaeng.2017.07.003

Cited by 30 publications

(10 citation statements)

References 27 publications

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“…According to Saberioon., et al (2017), [16] computer vision technology has been utilised to detect the presence, number, length, and behaviour of fish. Recent research has demonstrated that it can also be used to accurately feed fish by estimating their hunger [17,18]. The texture, colour, shape, area, and number of fish feeding simultaneously alter when fish exhibit different feeding intensities [19].…”

Section: Recognition Of Direct Feeding Behaviourmentioning

confidence: 99%

The Power of AI in Fish Feeding and Behavior Management: A Comprehensive Review

Pradhan¹

2023

Act Sci VetSci

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In this study, the use of computer vision and artificial intelligence technology is examined as a means of improving the efficacy and sustainability of fish feeding in aquaculture. The proposed approach employs machine learning techniques to estimate feeding requirements and optimise feeding schedules, while image analysis is employed to track fish behaviours and appetite. The method aims to increase the growth and health of fish while reducing waste and the environmental impact of aquaculture operations.

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Section: Recognition Of Direct Feeding Behaviourmentioning

confidence: 99%

The Power of AI in Fish Feeding and Behavior Management: A Comprehensive Review

Pradhan¹

2023

Act Sci VetSci

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“…Pada penelitian yang dilakukan oleh Fitri Muwardi, [3] untuk pendeteksi jenis bunga dengan kamera handphone berbasis Matlab dengan metode pegolahan citra dan pengklasifikasian jarak bisa menghasilakn akurasi 85% untuk metode jarak manhattan dan 77% metode jarak eucladian. Pada penelitian yang dilakukan oleh Qussay Al-Jubouri, [4] untuk mengukur panjang ikan zebra berbasis automated vision system menggunakan low-cost camera atau kamera WebCam . Penelitian yang dilakukan oleh Naijian Chen, [5] untuk mendeteksi defect yang terdapat pada kayu yang sulit di lihat oleh manusia menggunakan image recognition berbasis Jaringan Syaraf Tituan.…”

Section: Penelitian Terkaitunclassified

Perancangan Sistem Conformal Coating Inspection Circuit Board Menggunakan Metode Jaringan Saraf Tiruan Berbasis Matlab

Ramli¹,

Salamah

Yuliza

2021

JTE

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Masalah Human-Error pada process manual inspection seperti pada proses conformal coating circuit board menjadi hal yang harus diperhatikan mengingat sangat pentingnya fungsi dari conformal coating untuk melindungi circuit board dari oksidasi dan pengaruh lingkungan. Sehingga diperlukan suatu sistem inspection yang bisa menggantikan peran manusia dalam pengecekannya sehingga dapat menhilangkan masalah human-error. Salah satunya adalah dengan memanfaatkan computer vision yaitu cabang ilmu yang mempelajari tentang bagaimana suatu sistem dapat mengenali suatu objek dengan kombinasi antara pengolahan citra dan pengenalan pola. Untuk memastikan level inspection system tersebut sama dengan yang dilakukan manusia bisa menggunakan Jaringan syaraf Tiruan untuk proses pengambilan keputusan. Berdasarkan hal tersebut, pada penelitian ini dibuat suatu prototype conformal coating inspection menggunakan JST. Pada penelitian ini juga penulis mencoba mengolah data input JST dengan metode PCA (Principal Component Analysis). Proses percobaan pada sistem dilakukan dengan memberikan variasi pada epoch, learning rate dan hidden layer sehingga bisa dilihat hubungannya terhadap nilai RMSE, Processing time dan recognition rate. Berdasarkan hasil perancangan, implementasi dan pengujian yang dilakukan, maka dapat ditarik kesimpulan bahwa JST dengan PCA lebih baik dengan akurasi 100%. Pada tahap learning process nilai RMSE terendah yaitu 4 x 10-7, recognition rate 100% presentase 88.88%, dan Processing time tercepat 696.4910 detik

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“…The calculation method of transposed convolution is similar to convolution. The image size after transposed convolution is described in Equation (12).…”

Section: Fully Convolutional Networkmentioning

confidence: 99%

“…Tillett et al [11] proposed a three-dimensional point distribution model to capture the typical shape and variability of salmon viewed from the side and fit the model to the stereo image of the test fish by minimizing the probability distribution based energy function. Jubouri et al [12] proposed a low-cost computer vision system that uses dual-synchronized orthogonal web cameras to estimate the length of small fish. The contour and position of the fish body can be recognized by continuously capturing the front and side images of the studied fish.…”

Section: Introductionmentioning

confidence: 99%

Underwater Fish Body Length Estimation Based on Binocular Image Processing

Cheng

Zhang

et al. 2020

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Recently, the information analysis technology of underwater has developed rapidly, which is beneficial to underwater resource exploration, underwater aquaculture, etc. Dangerous and laborious manual work is replaced by deep learning-based computer vision technology, which has gradually become the mainstream. The binocular cameras based visual analysis method can not only collect seabed images but also construct the 3D scene information. The parallax of the binocular image was used to calculate the depth information of the underwater object. A binocular camera based refined analysis method for underwater creature body length estimation was constructed. A fully convolutional network (FCN) was used to segment the corresponding underwater object in the image to obtain the object position. A fish’s body direction estimation algorithm is proposed according to the segmentation image. The semi-global block matching (SGBM) algorithm was used to calculate the depth of the object region and estimate the object body length according to the left and right views of the object. The algorithm has certain advantages in time and accuracy for interest object analysis by the combination of FCN and SGBM. Experiment results show that this method effectively reduces unnecessary information, improves efficiency and accuracy compared to the original SGBM algorithm.

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An automated vision system for measurement of zebrafish length using low-cost orthogonal web cameras

Cited by 30 publications

References 27 publications

The Power of AI in Fish Feeding and Behavior Management: A Comprehensive Review

The Power of AI in Fish Feeding and Behavior Management: A Comprehensive Review

Perancangan Sistem Conformal Coating Inspection Circuit Board Menggunakan Metode Jaringan Saraf Tiruan Berbasis Matlab

Underwater Fish Body Length Estimation Based on Binocular Image Processing

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