Automated Germinationrate and Quality Evaluation of Rice Seedsusing Computer Vision and Machine Learning Algorithms

Good seed germination with high quality is critical for rice seed quality and production, which affects rice output and crop yield. Currently, paddy germination and quality evaluation are done manually by qualified individuals. Images of germinated rice seed are being captured on a daily basis. In this paper, we present a method for automatically evaluating the germination rate and quality of rice seeds that is based on sophisticated computer vision and machine learning algorithms. For rice seed detection, segmented areas will be subjected to processing such as calculating distance transform and thresholding.