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Paper Details

A Computer Vision Approach for Automated Cucumber Disease Recognition
Md. Abu Ishak Mahy, Joyanta Basak, Md. Jueal Mia , Salowa Binte Sohel, Sourov Mazumder,

Agriculture is the greatest labor agency in Bangladesh. As our country is an agricultural country, most of the people of Bangladesh depend on agricultural products for their livelihood. Lack of opportunities and facilities, natural disasters and diseases of crops are main obstacles in growth of agricultural sector in our country. Diseases in plants are significant hitch constraints the quality of crops. As important agricultural crops are under threat due to various plant diseases and pests, the quality of the crop can be affected by various diseases. So, it is very necessary to detect the disease at the proper period to the cultivator. When crop disease could be easily track out, it can be effective for monitoring and restrain disease for agriculture and food safety. We have worked with cucumber disease detection in our project because cucumber is a much needed grain in our country. If the cucumber is affected, it will cause a huge damage to the economy of the country. Since cucumber has many qualities, if it is transited, it will have a huge detrimental effect on nutrition. A system called computer vision and machine learning is used to detect crop diseases promptly and accurately which we used to detect cucumber diseases. Diagnosis of plant disease through this technology is very profitable and easy. This is because it reduces huge workload of crop monitoring and it can detect the symptoms of all diseases at a very early stage. This system includes pattern recognition and creating database and classification, approximation, optimization and data clustering. We are going to implement this goal by thinking of the people and helping the farmers to cultivate properly.

Agricultural crops, Computer vision, Cucumber diseases, Pattern recognition, Classification
Journal or Conference Name
Lecture Notes in Networks and Systems
Publication Year