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

Abstract

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.