Benjamaporn LurstwutChomtip PornpanomchaiMahidol University2018-12-212019-03-142018-12-212019-03-142017-10-01Agriculture and Natural Resources. Vol.51, No.5 (2017), 383-3892452316X2-s2.0-85044947922https://repository.li.mahidol.ac.th/handle/20.500.14594/41365© 2017 Kasetsart University Computer software—the Rice Seed Germination Evaluation System (RSGES)—was developed which can evaluate a rice seed image for germination prediction by using digital image processing and an artificial neural networks technique. The digital images are taken with a normal digital camera or mobile phone camera, which is very easy for farmers to process. RSGES consists of six main processing modules: 1) image acquisition, 2) image preprocessing, 3) feature extraction, 4) germination evaluation, 5) results presentation and 6) germination verification. The experiment was conducted on seed of the Thai rice species CP-111 in Bangkok and Chiang Mai, Thailand. RSGES extracted 18 features: 3 color features, 7 morphological features and 8 textural features. The system applied artificial neural network techniques to perform germination prediction. The system precision rate was 7.66% false accepted and 5.42% false rejected, with a processing speed of 8.31 s per image.Mahidol UniversityAgricultural and Biological SciencesArticleSCOPUS10.1016/j.anres.2017.12.002