Computer Vision Approach for Cucumber Disease Recognition

Abstract

Agriculture is the greatest labor agency in Bangladesh. As our country is an agricultural country; Most of the people of Bangladesh depends on agricultural products for their livelihood. Lack of opportunities and facilities, natural disasters, diseases of crops are main obstacles in growth of agricultural sector in our country. Diseases in plants are a significant yield and quality constraint for growers of broad acre crops. As important agricultural crops are under threat due to various plant diseases and pests and 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, then 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 much needed grain in our country. If the cucumber is affected, it will cause 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 disease 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 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.