- January 17, 2018
- Posted by: RSIS
- Categories: Electrical and Electronics Engineering, Electronics & Communication Engineering, Engineering, Image Processing
International Journal of Research and Scientific Innovation (IJRSI) | Volume V, Issue I, January 2018 | ISSN 2321–2705
A Survey on Region Identification of Rice Diseases Using Image Processing
Lipsa Barik#
#Department of Electronics, Sambalpur University / Sambalpur University Institute of Information Technology (SUIIT), India
Abstract— In this paper, we presents a rigorous survey on different image processing technique used to identify various rice leaf diseases. India is the second largest country producing of rice. An estimated 70% of indian economy depends on agriculture. Since, growing indian population, which is increasingly depends on the agriculture. Production of crops must be enhanced. A crops disease has financially strike the society. Crops diseases have caused huge economic losses in each countries. Normal human vision cannot detect the disease more accurately. Therefore, an alternative system is required. Where, a low cost but technology dependent system is required. The best alternative is nothing but image processing as it provides results than any other techniques.
Keywords— Plant leaf disease; feature extraction; image processing
I. INTRODUCTION
Rice is considered as the most important food crop all over the world. so, the crop losses in the developing countries like india which run to billions of dollars affect adversely the country economy and nutritional standard because almost 70% of the population of indian depend on it. These are different types of rice plants diseases with different symptoms. Observing the symptoms but due to changes of climate, biological condition and characteristics of the rice disease change with respect to time. Therefore, accurate and timely diagnosis of rice plant diseases is necessary and may play significant role in country’s economical growth. Rice covers about 69 percent of the cultivated area and is the major crop covering about 63 percent of total area under the food grains. The grain will be distinguished based on the shape analysis, texture analysis and edge detection of the grain. Rice disease diagnosis by soft computing technique is useful technology now days.
