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Automatic system for grading banana using GLCM texture feature extraction and neural network arbitrations
Author(s) -
Olaniyi Ebenezer O.,
Adekunle Adefemi A.,
Odekuoye Temitope,
Khashman Adnan
Publication year - 2017
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/jfpe.12575
Subject(s) - computer science , artificial neural network , support vector machine , food processing , artificial intelligence , backpropagation , grading (engineering) , feature extraction , image processing , pattern recognition (psychology) , engineering , image (mathematics) , chemistry , food science , civil engineering
Nowadays, an identification system is needed in the food processing industries to boost the efficiency of production so as to meet up with demand in the society. Manual approach is often used in product grading and quality control, and this unfortunately could lead to uneven products, higher time expense, and fatigue by the human operators. Therefore, we propose in this article, an automatic system for classification of banana whether it is healthy for production or not. Such a system is faster, accurate and also relieves the stress that an operator may have. Our system uses GLCM texture feature analysis to extract the features required for training and testing three classification models; namely, radial basis function (RBF), support vector machine (SVM), and backpropagation neural network (ANN). A classification performance comparison is drawn between the different classification models, and the obtained experimental results indicate that such intelligent grading systems may be efficiently used in real life applications for similar tasks in food processing industries. Practical applications The Automatic system is highly needed in food processing industries to meet up with the production of food products required in the societies. Healthy food products are needed in the society and this can be achieved by implementing a system that will enhance in the sorting or grading of the raw materials (such as banana) used in food processing industries. This system is accurate, economical, and faster in achieving the best product. Such a system will make the product be readily available in the market i.e. meeting the need of the people.