Jackfruit Disease Recognition Using Computer Vision

Abstract

Agriculture is the mother of all cultures. It has played an important role in the development of human civilization. Bangladesh economy depends on agriculture and a large number of people directly or indirectly related to this sector here. For this reason, the increasing demand in the agricultural industry, they need to effectively grow a plant and increase its yield is very important. In order to do that, it is important to monitor the field during its growth period, as well as, at the time of harvest. Fruit disease is crucial causes that which reduce quantity and can degrade the quality of the agricultural products. It is difficult and challenging to recognition the Jackfruit diseases manually. This paper represents various approaches for recognition and segmentation method along with image acquisition, pre-processing, segmentation, feature extraction and classification for recognize of diseases. This disease recognition system uses an image database for training and testing. The images are recognized to their respective disease categories on basis of different features such as contrast, correlation, energy, homogeneity, mean, standard deviation, entropy, variance, skewness. In our proposed system, we are going to develop an integrated image processing system to help automated inspection of jackfruit and helps identify the disease type. This prototype has a very great potential to be further improved in the future.