Image Processing of Vegetables and Predicting Disease
Kartik Kansal1, Tushar Gupta2, Archana Singh3, Rana Majumdar4
1Kartik Kansal, Information Technology, Amity University, Noida, India.
2Tushar Gupta, Information Technology, Amity University, Noida, India.
3Dr. Archana Singh, Professor, Information Technology, Amity University, Noida, India.
4Dr. Rana Majumdar, Associate Professor , Meghnad Saha Institute of Technology, Techno, India.
Manuscript received on 24 August 2019. | Revised Manuscript received on 06 September 2019. | Manuscript published on 30 September 2019. | PP: 3791-3797 | Volume-8 Issue-11, September 2019. | Retrieval Number: K21740981119/2019©BEIESP | DOI: 10.35940/ijitee.K2174.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Diseases present in vegetables as well as fruits are producing huge number of sufferings in the economic losses with addition to the losses of our agricultural industry worldwide. The main concern of this project is to understand various issues faced by the farmers in addition to consumer community also and hence to deliver a solution in regard to this major issue for farmers in detecting and classifying the category of the disease present in the vegetables and fruits. According to various studies we concluded that the diseases could occur through various aspects like viruses, fungus, bacteria etc. Hence as a result there is a great need to terminate such precious losses to the vegetables along with the farmers and in addition with the whole agricultural environment. Sometimes not only such aspects can cause damage to the vegetables but also there are many more reasons which are improper transportation of these vegetables from one origin to another, diverse climatic conditions could also be a reason of such causes. We have used python as a programming language with OpenCV library and HSV model of object detection to derive the optimal results. This library is used to perform several image manipulation operations. The dataset including numerous amount having traces of bacteria, fungi, etc. on vegetables are created. Then we implied HSV model which helps us to detect the spots or we can say traces of bacteria, fungi on the vegetables and hence the mask of that region is separated from the RGB image. GUI is created in python only which makes the program interactive with the user. Hence as a result we are able to see different types of spots for different type of disease.
Keywords: HSV model, Image manipulation, OpenCV, RGB image
Scope of the Article: Image Processing and Pattern Recognition.