Image analysis based on color, shape and texture for rice seed (Oryza sativa L.) germination evaluation

ผู้แต่ง

  • Benjamaporn Lurstwut Faculty of Information and Communication Technology, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pathom 73170, Thailand
  • Chomtip Pornpanomchai Faculty of Information and Communication Technology, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pathom 73170, Thailand

คำสำคัญ:

Artificial neural network, Digital image processing, Germination evaluation, Germination verification, Rice seeds

บทคัดย่อ

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.

ดาวน์โหลด

เผยแพร่แล้ว

2017-10-31

รูปแบบการอ้างอิง

Lurstwut, Benjamaporn, และ Chomtip Pornpanomchai. 2017. “Image analysis based on color, shape and texture for rice seed (Oryza sativa L.) germination evaluation”. Agriculture and Natural Resources 51 (5). Bangkok, Thailand:383-89. https://li01.tci-thaijo.org/index.php/anres/article/view/239944.

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ประเภทบทความ

Research Article