A brief study on paddy applications with image processing and proposed architecture

Agriculture industry is one of the main economic activities in Asean countries. The activities involved a lot of crop planting and yield production in paddy, rubber, oil palm and so forth. Meanwhile in Malaysia, paddy is the third most widely planted crop after oil palm and rubber. Rice, produced by paddy, is considered to be one of Malaysia and Asean staple food and cereal crops. Due to its importance, there are a lot of efforts to ensure its safety, by having crop management of paddy plants such as, disease early detection system. The conventional way to detect plant defects is through human vision and it requires deep knowledge and understanding of the plant. The knowledge is gained through years of experience and observation. Therefore, the intelligent methods in this research are expected to assist the farmers in identifying leaf diseases. In this paper, we present the studies that deployed image processing technologies in paddy domain. Subsequently, we propose the architecture of our system for identifying the early stage of the leaf diseases and finding the weed species. The proposed system is expected to reduce the risk of diseases from becoming worse which may minimize the paddy yields.