There are many types of insects that affect agricultural fields. These harmful insects should be classified in a smart implementation for the rural fields. The main point to detect depends on their texture color. These textures are different
from one insect to another. We propose a new hybrid method based on Gray Level Co-occurrence Matrix (GLCM) to detect the harmful insects in agricultural fields. The main idea shows that a tested image is composed of different texture regions of the insect and this will help to extract feature value. This paper consists of three steps: the first step extracts texture features using
GLCM in four directions which are 0, 90, 180 and 270 degrees from the gray image. The second step trains the neural network depending on texture features in a large number of variety insect’s images. The third step tests the unknown insect s image to classify it whether harmful or not. The purpose of this study helps rural farmers to detect the harmful insects and classify them to take care of
their crops.
There are many efforts that need to be achieved to help the farmers in the rural areas. The technology tool has been used in this area to help people to achieve their work smoothly and in an easy way. Achievement of agricultural development in the 21st century depends on the wide use of information and communication technology. Most efforts in rural areas have been concerned in
the training courses using ICT [1]. Supporting rural work using different technologies is a good way to increase their skills in agricultural fields. Based on this, we need to build a good tool that recognizes the insects in the agricultural
field based on the insects’ texture color. There are different fields in image processing help to detect the object. This
paper introduces a new hybrid of insect’s recognition which is part of image processing using Gray level co-occurrence matrix (GLCM). This helps people in agricultural field to know more information about the harmful insects. This paper uses the combination of the GLCM algorithm and neural network. The neural network inputs depend on the extraction of texture features in different directions based on GLCM of different image patterns.