Publication: Image analysis based on color, shape and texture for rice seed (Oryza sativa L.) germination evaluation
8
Issued Date
2017-10-01
Resource Type
ISSN
2452316X
Other identifier(s)
2-s2.0-85044947922
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Agriculture and Natural Resources. Vol.51, No.5 (2017), 383-389
Suggested Citation
Benjamaporn Lurstwut, Chomtip Pornpanomchai Image analysis based on color, shape and texture for rice seed (Oryza sativa L.) germination evaluation. Agriculture and Natural Resources. Vol.51, No.5 (2017), 383-389. doi:10.1016/j.anres.2017.12.002 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/41365
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Image analysis based on color, shape and texture for rice seed (Oryza sativa L.) germination evaluation
Author(s)
Other Contributor(s)
Abstract
© 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.