Recent Developments in the Quality Evaluation of Rice Disease Detection System

The recent progress in the field of computer vision has facilitated the implementation of diverse applications across several domains of human existence. One notable domain of application pertains to the classification of plant diseases, with a particular focus on rice plants. However, the classification of rice plants has shown itself as a multifaceted challenge, necessitating additional advancements in this field. The classification of rice diseases poses considerable difficulties as a result of similarities between different classes and the irregular characteristics within each class. The careful selection of data acquisition sensors and the adoption of an appropriate feature representation approach are of utmost importance in light of the extensive range of applications in this field. In recent years, there has been a growing utilisation of computer vision techniques for the purpose of evaluating food quality. This paper provides an overview of the current advancements in techniques and their application in conjunction with diverse sensing devices for the purpose of detecting plant problems. The identification and resolution of significant challenges related to defect detection in rice plants entail different technical obstacles. This study provides an overview of the latest developments in computer vision methodologies used for assessing the quality of rice plants. This study showcases the potential of image processing techniques in the assessment of rice plant quality. Additionally, it highlights several unresolved difficulties that require additional investigation to facilitate the widespread implementation of image processing technology for evaluating the quality of rice plants.