ORYZA: AN IOT APPLICATION TO DETECT RICE CROP DISEASES USES IMAGE PROCESSING
JYOTHI MAADUGUNDU
, AJAY KUMAR , SIRISHA
Internet of Things, Image Processing, Rice crop disease detection, Haralick’s texture feature matrix
Being an agricultural country, most of the people of Bangladesh are dependent on agriculture directly or indirectly. It is the fourth largest rice producing country in the world. Main hindrance in rice production is paddy diseases. So in this research the main objective is to develop a prototype system for detecting the paddy diseases, which are Paddy Blast, Brown Spot and Narrow Brown Spot diseases. This concentrate on the image processing techniques used to find pattern in the image and artificial neural network technique to classify the diseases. The methodology involves image collection, image processing, feature extraction and classification. Features are extracted from the images using Haralick’s texture feature from color co-occurrence matrix. Then an artificial neural network is trained by these features and a trained model is found. In testing phase, all paddy samples are passed through the leaf color analysis to detect the normal paddy leaf image. If the sample passes leaf color analysis, then it is automatically classified as Normal Paddy leaf image. Otherwise, all the segmented paddy disease samples are converted into the features data and are passed through the artificial neural network. Consequently, by employing the artificial neural network technique, the paddy diseases are recognized. The accuracy to detect diseases of this model is good enough to use in practical life.
"ORYZA: AN IOT APPLICATION TO DETECT RICE CROP DISEASES USES IMAGE PROCESSING", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.4, Issue 12, page no.190 - 197, December-2019, Available :https://ijsdr.org/papers/IJSDR1912041.pdf
Volume 4
Issue 12,
December-2019
Pages : 190 - 197
Paper Reg. ID: IJSDR_191192
Published Paper Id: IJSDR1912041
Downloads: 000347406
Research Area: Engineering
Country: HYDERABAD, telangana, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
