Ripeness Classification of Bananas Using an Artificial Neural Network
| العنوان: | Ripeness Classification of Bananas Using an Artificial Neural Network |
|---|---|
| المؤلفون: | Fatma Mazen Ali Mazen, Ahmed A. Nashat |
| المصدر: | Arabian Journal for Science and Engineering. 44:6901-6910 |
| بيانات النشر: | Springer Science and Business Media LLC, 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Multidisciplinary, Artificial neural network, Computer science, business.industry, media_common.quotation_subject, 010102 general mathematics, Decision tree, Pattern recognition, Ripening, Ripeness, Linear discriminant analysis, 01 natural sciences, Support vector machine, Naive Bayes classifier, Quality (business), Artificial intelligence, 0101 mathematics, business, media_common |
| الوصف: | The quality of fresh banana fruit is a main concern for consumers and fruit industrial companies. The effectiveness and fast classification of banana’s maturity stage are the most decisive factors in determining its quality. It is necessary to design and implement image processing tools for correct ripening stage classification of the different fresh incoming banana bunches. Ripeness in banana fruit generally affects the eating quality and the market price of the fruit. In this paper, an automatic computer vision system is proposed to identify the ripening stages of bananas. First, a four-class homemade database is prepared. Second, an artificial neural network-based framework which uses color, development of brown spots, and Tamura statistical texture features is employed to classify and grade banana fruit ripening stage. Results and the performance of the proposed system are compared with various techniques such as the SVM, the naive Bayes, the KNN, the decision tree, and discriminant analysis classifiers. Results reveal that the proposed system has the highest overall recognition rate, which is 97.75%, among other techniques. |
| تدمد: | 2191-4281 2193-567X |
| DOI: | 10.1007/s13369-018-03695-5 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::aecd78a346d72802c583054b9e4fb708 https://doi.org/10.1007/s13369-018-03695-5 |
| Rights: | CLOSED |
| رقم الانضمام: | edsair.doi...........aecd78a346d72802c583054b9e4fb708 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 21914281 2193567X |
|---|---|
| DOI: | 10.1007/s13369-018-03695-5 |