Radial Basis Function Neural Network in Identifying The Types of Mangoes

Thaib, Faisal and Tomasila, Golda and Nivaan, Goldy Valendria and Santoso, Albertus Joko (2020) Radial Basis Function Neural Network in Identifying The Types of Mangoes. In: The 8th International Conference on Information Technology iCoiCT 2020. Telkom University, Bandung, Indonesia.

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Text (Faisal Thaib, Golda Tomasila, Goldy Valendria Nivaan and Albertus Joko Santoso) 31. Radial Basis Function Neural Network in Identifying the Types of Mangoes.pdf Download (1MB) | Preview

Abstract

Mango (Mangifera Indica L) is part of a fruit plant species that have different color and texture characteristics to indicate its type. The identification of the types of mangoes uses the manual method through direct visual observation of mangoes to be classified. At the same time, the more subjective way humans work causes differences in their determination. Therefore in the use of information technology, it is possible to classify mangoes based on their texture using a computerized system. In its completion, the acquisition process is using the camera as an image processing instrument of the recorded images. To determine the pattern of mango data taken from several samples of texture features using Gabor filters from various types of mangoes and the value of the feature extraction results through artificial neural networks (ANN). Using the Radial Base Function method, which produces weight values, is then used as a process for classifying types of mangoes. The accuracy of the test results obtained from the use of extraction methods and existing learning methods is 100%.

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