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%.