Computer vision system for egg volume prediction using backpropagation neural network

Siswantoro, Joko; Hilman, M.Y.; Widiasri, Monica

doi:10.1088/1757-899x/245/1/012002

Cited by 13 publications

(15 citation statements)

References 8 publications

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“…Computer Vision dapat digunakan untuk menentukan volume atau luas suatu benda dengan bantuan algoritma seperti Aturan Simpson atau metode trapesium [11]. Metode ini telah digunakan untuk menentukan volume telur menggunakan jaringan syaraf tiruan (ANN) [12]. Metode aturan Simpson merupakan salah satu metode numerik yang dapat digunakan menentukan volume suatu benda.…”

Section: Pendahuluanunclassified

“…Kemudian langkah berikutnya adalah menentukan jumlah segmen pembagi permukaan citra 2D buah. Volume dari masing-masing segmen ditentukan dengan metode aturan Simpson 1/3 berdasarkan prinsip integrasi volume benda putar menggunakan Persamaan (5) [12] yang diturunkan dari Persamaan (3) dan Persamaan (4) [17]. Volume buah kiwi ditentukan dengan menjumlahkan volume dari masing-masing segmen atau cacahan.…”

Section: Konversi Pixel Ke CMunclassified

“…Perbedaan ini dapat disebabkan karena keakuratan metode Simpson dengan pendekatan elipsoida yang telah digunakan untuk menentukan volume buah kiwi. Sampel buah kiwi yang digunakan tidak sepenuhnya berbentuk persis elipsoida [17] tidak seperti hal telurnya atau lambung kapal yang dapat didekati dengan bentuk elipsoida [12], [13]. Namun metode pencitraan dengan Computer Vision telah dapat digunakan untuk menentukan volume buah kiwi secara nondestruktif sebagai alternatif mengantikan metode perpindahan air sehingga dapat digunakan dalam proses penyortiran buah mengunakan parameter volume.…”

Section: Hasil Dan Pembahasanunclassified

“…Tabel 1 adalah keterangan masing-masing parameter tersebut. Parameter penentuan volume buah kiwi[12],[13]…”

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Estimasi Volume Buah Kiwi Menggunakan Metode Pencitraan dan Aturan Simpson

Suherly

Shiddiq

2020

mib

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Volume is one of important quantities that have been applied to fruit sorting based on size. Imaging method or computer vision is a simple non destructive method that has been proposed to measure fruits volume. This study was aimed to estimate the volumes of kiwi fruits using Computer Vision imaging method and compared to a water displacement method. The samples were 20 green kiwi fruits (Actinidia deliciosa). A smartphone camera was used to record the kiwifruit images and Python based program to drive the camera and process the images. Images resulted in Computer Vision are two dimensions (2D) images. The 1/3 rd Simpson rule was employed to determine the volume of kiwi fruits based on the volume integration of a spinning object where surface image of kiwi was divided into 8 parts and then summed. The results show that the 2D imaging method assisted by the Simpson rule was successfully able to determine the kiwi fruit volumes with 4.57 % average difference percentage compared to the water displacement method. This was about 4.97 cm3 of average volume difference of 20 samples. The sample volumes measured using this method ranges from 82,48 cm3 - 126,85 cm3. These results will be one of steps toward the development of machine vision for fruit sorter based on volume

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Section: Pendahuluanunclassified

Section: Konversi Pixel Ke CMunclassified

Section: Hasil Dan Pembahasanunclassified

“…Tabel 1 adalah keterangan masing-masing parameter tersebut. Parameter penentuan volume buah kiwi[12],[13]…”

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Estimasi Volume Buah Kiwi Menggunakan Metode Pencitraan dan Aturan Simpson

Suherly

Shiddiq

2020

mib

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“…In this study, RSM is a mathematical modelling used to develop an empirical model and to perform optimization [36], whereas the artificial neural network is a soft computing technique which imitates the biological processing ability of the human brain [37,38]. Artificial neural networks have been applied in numerous studies due to its capability to handle modelling and simulation of complex nonlinear systems [39][40][41]. However, several references reported that artificial neural networks have better performance in prediction effectiveness compare to response surface methodology [42,43].…”

Section: Introductionmentioning

confidence: 99%

The Effect of Multi-Walled Carbon Nanotubes-Additive in Physicochemical Property of Rice Brand Methyl Ester: Optimization Analysis

et al. 2019

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Biodiesel as an alternative to diesel fuel produced from vegetable oils or animal fats has attracted more and more attention because it is renewable and environmentally friendly. Compared to conventional diesel fuel, biodiesel has slightly lower performance in engine combustion due to the lower calorific value that leads to lower power generated. This study investigates the effect of multi-walled carbon nanotubes (MWCNTs) as an additive to the rice bran methyl ester (RBME). Artificial neural network (ANN) and response surface methodology (RSM) was used for predicting the calorific value. The interaction effects of parameters such as dosage of MWCNTs, size of MWCNTs and reaction time on the calorific value of RBME were studied. Comparison of RSM and ANN performance was evaluated based on the correlation coefficient (R2), the root mean square error (RMSE), the mean absolute percentage error (MAPE), and the average absolute deviation (AAD) showed that the ANN model had better performance (R2 = 0.9808, RMSE = 0.0164, MAPE = 0.0017, AAD = 0.173) compare to RSM (R2 = 0.9746, RMSE = 0.0170, MAPE = 0.0028, AAD = 0.279). The optimum predicted of RBME calorific value that is generated using the cuckoo search (CS) via lévy flight optimization algorithm is 41.78 (MJ/kg). The optimum value was obtained using 64 ppm of < 7 nm MWCNTs blending for 60 min. The predicted calorific value was validated experimentally as 41.05 MJ/kg. Furthermore, the experimental results have shown that the addition of MWCNTs was significantly increased the calorific value from 36.87 MJ/kg to 41.05 MJ/kg (11.6%). Also, the addition of MWCNTs decreased flashpoint (−18.3%) and acid value (−0.52%). As a conclusion, adding MWCNTs as an additive had improved the physicochemical properties characteristics of RBME. To our best knowledge, no research has yet been performed on the effect of multi-walled carbon nanotubes-additive in physicochemical property of rice brand methyl ester application so far.

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Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review

et al. 2019

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Food safety issues across the global food supply chain have become paramount in promoting public health safety and commercial success of global food industries. As food regulations and consumer expectations continue to advance around the world, notwithstanding the latest technology, detection tools, regulations and consumer education on food safety and quality, there is still an upsurge of foodborne disease outbreaks across the globe. The development of the Electronic nose as a noninvasive technique suitable for detecting volatile compounds have been applied for food safety and quality analysis. Application of E-nose for pathogen detection has been successful and superior to conventional methods. E-nose offers a method that is noninvasive, fast and requires little or no sample preparation, thus making it ideal for use as an online monitoring tool. This manuscript presents an indepth review of the application of electronic nose (E-nose) for food safety, with emphasis on classification and detection of foodborne pathogens. We summarise recent data and publications on foodborne pathogen detection (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018) and by E-nose together with their methodologies and pattern recognition tools employed. E-nose instrumentation, sensing technologies and pattern recognition models are also summarised and future trends and challenges, as well as research perspectives, are discussed.

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Computer vision system for egg volume prediction using backpropagation neural network

Cited by 13 publications

References 8 publications

Estimasi Volume Buah Kiwi Menggunakan Metode Pencitraan dan Aturan Simpson

Estimasi Volume Buah Kiwi Menggunakan Metode Pencitraan dan Aturan Simpson

The Effect of Multi-Walled Carbon Nanotubes-Additive in Physicochemical Property of Rice Brand Methyl Ester: Optimization Analysis

Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review

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