The use of seed texture features for discriminating different cultivars of stored apples |
| |
| Affiliation: | 1. Henan University of Technology, Zhengzhou, 450001, China;2. Xi’an Jiaotong University, Xian, 710000, China;1. Department of Zoology, University of the Punjab, Quaid-i-Azam Campus, Lahore, Pakistan;2. Faculty of Life Sciences, University of the Central Punjab, Khiyaban-i-Jinnah, Johar Town, Lahore, Pakistan;3. School of Biological Sciences, University of the Punjab, Quaid-i-Azam Campus, Lahore, Pakistan;1. Department of Soil Science & Agricultural Engineering, University of Zimbabwe, Box MP 167, Harare, Zimbabwe;2. Institute of Food, Nutrition and Family Sciences, University of Zimbabwe, Box MP 167 Harare, Zimbabwe;3. Natural Resources Institute, University of Greenwich, Central Avenue, Chatham Maritime, Kent, ME4 4TB, UK;4. Department of Agricultural Economics and Extension, University of Zimbabwe, Box MP 167, Harare, Zimbabwe;1. Department of Systems Engineering, Faculty of Engineering, University of Warmia and Mazury in Olsztyn, Heweliusza 14, 10-718 Olsztyn, Poland;2. Department of Agrotechnology, Agricultural Production Management and Agribusiness, Faculty of Environmental Management and Agriculture, University of Warmia and Mazury in Olsztyn, M. Oczapowskiego 8, 10-719 Olsztyn, Poland;1. Department of Plant Sciences, Faculty of Agriculture, Rajarata University of Sri Lanka, Puliyankulama, Anuradhapura, Sri Lanka;2. Department of Agric. Biology, Faculty of Agriculture, University of Ruhuna, Mapalana, Kamburupitiya, Sri Lanka;3. Department of Biological Sciences, Faculty of Applied Sciences, Rajarata University of Sri Lanka, Mihintale, Sri Lanka;4. USDA, Agricultural Research Service, Center for Grain and Animal Health Research, 1515 College Ave., Manhattan, KS, 66052, USA;1. Plant Protection Laboratory, Department of Agriculture, University of Patras, Theodoropoulou Terma, 27200, Amaliada, Greece;2. Laboratory of Agricultural Zoology and Entomology, Department of Crop Science, Agricultural University of Athens, 75 Iera Odos str., 11855, Athens, Attica, Greece |
| |
| Abstract: | The aim of this study was to identify the textural features of apple seeds with the highest discriminatory power for distinguishing the seeds of different apple cultivars with the use of discriminative classifiers. The seeds of apple cvs. Gala, Jonagold and Idared were scanned with the use of a flatbed scanner, and the acquired images were processed to calculate textural features from color channels: L, a, b, R, G, B, Y, U, V, H, S, I, X, Y and Z. The selected textures were used to develop discriminative models and distinguish the seeds of the examined apple cultivars. The analyses were performed for color spaces and color channels. The seeds of apple cvs. Gala and Idared were discriminated with 100% accuracy in models based on the textures from Lab and YUV color spaces and color channel L for the Naive Bayes, Multilayer Perceptron and Multi Class classifiers. The discriminatory accuracies of the seeds of all analyzed apple cultivars (Gala, Idared and Jonagold) ranged from 72% to 85%. The discriminatory accuracy of the textures selected from Lab color space for the Naive Bayes classifier reached 85%. The seeds of apple cvs. Gala and Jonagold were discriminated with 78–90% accuracy, and the discriminatory accuracy of the textures from Lab color space and color channel b for the Naive Bayes classifier reached 90%. The seeds of apple cvs. Idared and Jonagold were distinguished with 80–94% accuracy. The models based on textures from Lab color space and color channel b for the Naive Bayes classifier were characterized by 94% discriminatory accuracy. The study demonstrated that textural features are useful for discriminating the seeds of different apple cultivars. |
| |
| Keywords: | Image analysis Textural features Apple seeds Discriminative classifiers |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
