Nondestructive Identification of Cherry-Tomato Varieties Based on Multi-Spectral Image Technology
| Autor: | Yong He, Lei Feng, Shuang Shuang Chen, Kai Sheng Yang, Peng Cheng Nie |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Engineering
biology business.industry General Engineering Pattern recognition Multi spectral Mathematical morphology Linear discriminant analysis biology.organism_classification Image (mathematics) Support vector machine Identification (information) Cherry tomato Segmentation Artificial intelligence business |
| Zdroj: | Advanced Materials Research. :262-267 |
| ISSN: | 1662-8985 |
| DOI: | 10.4028/www.scientific.net/amr.108-111.262 |
| Popis: | Yunnan cherry-tomato and Xinjiang cherry-tomato were very similar in appearance. But they are different in taste and nutritive value. A nondestructive identification method of cherry-tomato variety based on multi-spectral image technology is proposed in this paper. Fifty Yunnan cherry-tomatoes and fifty Xinjiang cherry-tomatoes were selected, and photos were taken by Duncan MS3100 3CCD multi-spectral imager. Threshold based segmentation and mathematical morphology method were used to process the images. Nine characteristic variables were calculated to establish discriminant analysis model (DA) and least square-support vector machine model (LS-SVM). The prediction accuracy of discriminant analysis model was 72.5% and that of LS-SVM model was 80%. The results showed that LS-SVM model could identify Yunnan cherry-tomato and Xinjiang cherry-tomato well. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|