Weeds identification in corn fields based on image processing techniques and artificial neural networks

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Dashti Abdol Hosein; OVEISI MOSTAFA; RAHIMIAN MASHHADI HAMID; ALIZADEH HASSAN

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Journal: IRANIAN JOURNAL OF WEED SCIENCE Year:2020 | Volume:15 | Issue:2 Page(s): 93-107

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Title

Weeds identification in corn fields based on image processing techniques and artificial neural networks

Author(s)

Dashti Abdol Hosein | OVEISI MOSTAFA | RAHIMIAN MASHHADI HAMID | ALIZADEH HASSAN | Issue Writer Certificate

Keywords

Herbicide applicationQ2

machine visionQ1

patch sprayingQ2

precision agricultureQ1

weedQ2

Abstract

weeds normally grow as patches and spatially distributed in field. patch spraying to control weeds has advantages such as cost reduction, herbicide saving and reduction of environmental pollution. machine vision system should obtain and process digital images to make control decisions. Proper identification and classification of weeds are the key steps to make control decisions and use of any spraying operation performed. In this study, a robust method based on image processing and computational intelligence was developed for segmentation from other parts of image and classification of weeds. Large crabgrass, common lamb’ s quarter, velvetleaf, common barnyard grass, European black nightshade, red-rooted pigweed and European heliotrope were the weeds in the experiment. Results showed that this algorithm was precisely separated weeds from the soil. In the next step, the feature vector, which includes shape features and color features, was composed. Finally, classification of seven classes of weeds was carried out by artificial neural network (ANN). Among different ANN structures, the most optimum classifier was the 43-15-15-7 topology with accuracy 88/71 %. The results of this research indicate that the proposed system has the ability to accurately detection of weeds.

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APA: Copy

Dashti, Abdol Hosein, OVEISI, MOSTAFA, RAHIMIAN MASHHADI, HAMID, & ALIZADEH, HASSAN. (2020). Weeds identification in corn fields based on image processing techniques and artificial neural networks. IRANIAN JOURNAL OF WEED SCIENCE, 15(2 ), 93-107. SID. https://sid.ir/paper/389378/en

Vancouver: Copy

Dashti Abdol Hosein, OVEISI MOSTAFA, RAHIMIAN MASHHADI HAMID, ALIZADEH HASSAN. Weeds identification in corn fields based on image processing techniques and artificial neural networks. IRANIAN JOURNAL OF WEED SCIENCE[Internet]. 2020;15(2 ):93-107. Available from: https://sid.ir/paper/389378/en

IEEE: Copy

Abdol Hosein Dashti, MOSTAFA OVEISI, HAMID RAHIMIAN MASHHADI, and HASSAN ALIZADEH, “Weeds identification in corn fields based on image processing techniques and artificial neural networks,” IRANIAN JOURNAL OF WEED SCIENCE, vol. 15, no. 2 , pp. 93–107, 2020, [Online]. Available: https://sid.ir/paper/389378/en

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