PLANT DISEASE DETECTION USING IMAGE SEGMENTATION & CONVOLUTIONAL NEURAL NETWORK

Abstract

Identifying regions in an image and labeling them to class is called image segmentation. Automatic image segmentation has been one of the major research areas which is in trend nowadays. Every other day a new model is being discovered to do better image segmentation for the task of computer vision. As the better a computer is able to see, the better we can automate the tasks around our daily life. In this survey we are comparing various image segmentation techniques and on the basis of our research we are applying the best approach to an application i.e. developing a model to identify diseased plants and to give an idea to the people what kind disease is present in a plant. The detailed analysis of the methodology is done with the help of various analysis techniques, which are used in reference to the context of the work. Our focus is on the techniques which we are able to optimize and make them better than the one which are present before. This survey emphasizes on the importance of application of image segmentation techniques and to make them more useful for the common public in daily life. So that they get benefits of this technology in the monitoring of any activity occurring around that can’t be done manually.