Toward an automatic wheat purity measuring device: A machine vision-based neural networks-assisted imperialist competitive algorithm approach |
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| Affiliation: | 1. Department of Mechanical Engineering of Agricultural Machinery, Faculty of Agriculture, Islamic Azad University, Kermanshah Branch, Kermanshah, Iran;2. Department of Biosystems Engineering, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran;3. Department of Agronomy and Plant Breeding, Faculty of Agricultural Science and Engineering, University of Tehran, Karaj, Iran;1. Department of Mechatronics and Technical and IT Education, Faculty of Technical Science, University of Warmia and Mazury, Sloneczna 46A, 10-710 Olsztyn, Poland;2. Department of Mathematics and Computer Science, University of Warmia and Mazury, Sloneczna 54, 10-710 Olsztyn, Poland;3. Institute of Electronics, Lodz University of Technology, Wolczanska 211/215, 90-924 Lodz, Poland;1. Institute of Electronics, Lodz University of Technology, Wolczanska 211/215, 90-924 Lodz, Poland;2. Department of Agri-Food Process Engineering, University of Warmia and Mazury in Olsztyn, Heweliusza 14, 10-718 Olsztyn, Poland;1. Embrapa Agricultural Informatics, Av. André Tosello, 209, C.P. 6041, Campinas 13083-886, SP, Brazil;2. Embrapa Wheat, Rodovia BR-285, Km 294, C.P. 3081, Passo Fundo 99001-970, RS, Brazil;1. Department of Crop Production and Plant Breeding, Faculty of Agriculture, Bu Ali Sina University, Hamadan, Islamic Republic of Iran;2. Department of Agronomy and Plant Breeding, Faculty of Agricultural Science & Engineering, University of Tehran, Karaj, Islamic Republic of Iran;1. Academy of Scientific and Innovative Research (AcSIR), Central Scientific Instruments Organisation, Sector 30-C, Chandigarh 160030, India;2. CSIR-Central Scientific Instruments Organisation, Sector 30-C, Chandigarh 160030, India |
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| Abstract: | Wheat product quality is closely related to wheat seed purity. Purity is an important factor that has a considerable impact on wheat product prices in grain storage silos. The aim of this paper was to introduce a machine vision based approach as a primarily step for fabricating an automatic wheat purity determination and grading device. Experimental data consists of 52 color, morphology, and texture characteristic parameters, extracted from images of samples, including four local wheat grades and eight common weed seeds growing in wheat fields of Iran, were used to build the classification models. A new algorithm that combines Imperialist Competitive Algorithm (ICA) and Artificial Neural Networks (ANNs) has been used for two purposes: to find the best characteristic parameters set and to create robust classification models. Based upon the results obtained from this study, the total classification rate of ICA–ANN approach for wheat grains vs. non-wheat seeds, wheat grain classes, and non-wheat seed classes was 96.25%, 87.50%, and 77.22%, respectively. |
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| Keywords: | ANN Cereal Classification ICA Image processing Weed seed |
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