IDENTIFICATION OF AMARANTHUS SPP. SEED USING MACHINE VISION AND ARTIFICIAL NEURAL NETWORK

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EGHBALI L.; SADRABADI HAGHIGHI R.; MOIN RAD H.; BAGHERI A.R.

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Paper Information

Journal: SEED RESEARCH (JOURNAL OF SEED SCIENCE AND TECHNOLOGY) Year:2013 | Volume:3 | Issue:2 Page(s): 74-85

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Information Journal Paper

Title

IDENTIFICATION OF AMARANTHUS SPP. SEED USING MACHINE VISION AND ARTIFICIAL NEURAL NETWORK

Author(s)

EGHBALI L. | SADRABADI HAGHIGHI R. | MOIN RAD H. | BAGHERI A.R. | Issue Writer Certificate

Keywords

ARTIFICIAL NEURAL NETWORKQ3

IMAGE PROCESSINGQ2

SEED CLASSIFICATIONQ2

TUMBLEWEEDQ2

Abstract

In order to identify and classify the seeds of three species of genus Amaranthus including Amaranthus albus, Amaranthus retroflexus and Amaranthus viridis an experiment was conducted using machine vision and ARTIFICIAL NEURAL NETWORK in 2011. Quantified information about the characteristics of each seed was extracted, after taking images of the seeds. After that neural networks were constructed using original and normalized data. Results showed that the Multilayer Perceptron neural networks with the transfer function of TanhAxon and Momentum learning rule were the best neural networks. Overall accuracy of identification of neural networks constructed from the original data of the fifteen predictor variables were 74.75%. The values for the neural network which constructed form predictor variable that suggested by stepwise were 76.26%. Overall accuracy of identification of neural networks constructed from the normal data of the fifteen predictor variables were 82.00%. The values for the neural network which constructed form normal data of the predictor variable that suggested by stepwise regression were 79.81%. In general, using morphological characteristics of seeds for classifying Amaranthus species was relatively acceptable. Using other morphological, color and texture characteristics of the seeds were advised to increase identification and classification accuracy.

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APA: Copy

EGHBALI, L., SADRABADI HAGHIGHI, R., MOIN RAD, H., & BAGHERI, A.R.. (2013). IDENTIFICATION OF AMARANTHUS SPP. SEED USING MACHINE VISION AND ARTIFICIAL NEURAL NETWORK. SEED RESEARCH (JOURNAL OF SEED SCIENCE AND TECHNOLOGY), 3(2), 74-85. SID. https://sid.ir/paper/226617/en

Vancouver: Copy

EGHBALI L., SADRABADI HAGHIGHI R., MOIN RAD H., BAGHERI A.R.. IDENTIFICATION OF AMARANTHUS SPP. SEED USING MACHINE VISION AND ARTIFICIAL NEURAL NETWORK. SEED RESEARCH (JOURNAL OF SEED SCIENCE AND TECHNOLOGY)[Internet]. 2013;3(2):74-85. Available from: https://sid.ir/paper/226617/en

IEEE: Copy

L. EGHBALI, R. SADRABADI HAGHIGHI, H. MOIN RAD, and A.R. BAGHERI, “IDENTIFICATION OF AMARANTHUS SPP. SEED USING MACHINE VISION AND ARTIFICIAL NEURAL NETWORK,” SEED RESEARCH (JOURNAL OF SEED SCIENCE AND TECHNOLOGY), vol. 3, no. 2, pp. 74–85, 2013, [Online]. Available: https://sid.ir/paper/226617/en

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