Research on varietal classification and germination evaluation system for rice seed using hand-held devices

Abstract

Rice Seed varietal classification and germination evaluation system is developed to identify the variety and evaluate the germination of rice seeds using Digital Image processing system. For economic and ease of usage, we have used mobile phones to take digital images. The objective of our research is, it will be easily used by farmers. Our research is done on four major rice varieties, which commonly cultivated by Tamilnadu farmers, namely (1) Andhra Ponni (2) Atchaya Ponni (3) KO50 and (4) IR 20 was collected from Tamilnadu Agricultural University Tiruchirappalli, Tamilnadu, India. We have extracted 24 features: 3 colour features, 13 morphological features and 8 textural features. Created data set tested with all possible classification algorithms, out of which Ensemble classification algorithm gives 91.6% accuracy for Variety Identification and SVM gives 63% of accuracy for germination prediction. According to the germination percentage, a support vector machine (SVM) was utilised to categorise the seeds specimens into 3 groups: healthy, old, and deceased. The categorisation prediction accuracy has always been significant. We have created the data set for successful identification of varieties and germination prediction for the above-mentioned varieties; it is publicly available for usage.