Disease diagnosis in crops using content based image retrieval

Farmers always need satisfactory and easy advice from experts. To get the advice from an expert system, it should have enough knowledge about the domain. Gathering enough knowledge and representing it in a machine understandable format is time consuming and difficult job. Also, representing each and every kind of knowledge is still a research issue. Since, a single picture is worth a thousand words, it will be a good idea to acquire knowledge also in images rather than only text. Image is an easy way of communication without any boundary of language. Hence there is a need for building an expert system with content based image retrieval which could acquire and deliver the knowledge by searching the image having the similar features that is searched by the user. In the presented work, a system is developed to diagnose diseases in crops by matching the uploaded image of a diseased plant from the corpus of images. Three techniques viz. CEDD, Auto Color Correlogram and FCTH are tested and the result is presented. The automatic image based disease diagnosis in crops may help farmers in early detection of diseases and losses due to the image infestation can be reduced.