- 期刊
- OpenAccess
Fruit Color Recognition Based on Multiple Classifier Combination
並列摘要
In this study, we propose a method of fruit color recognition based on multiple classifier combination. Firstly, color type is defined based on human eye sensation and then HSV color space and classification algorithms are adopted via statistical of large fruit samples. For distinguished fruit color types, support vector machine algorithm is used for classification. After generating prior probability and class conditional probability, maximum posterior probability is computed based on Bayesian classifier to identify color types for less-distinguishable colors type. At Last support, vector machine and Bayesian classifier are combined to form a decision tree, which is then simplified to binary classifier problem. Experiment results show that average recognition rate of fruit color is about 86.5%.
延伸閱讀
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- 彭雅芳（2019）。Automatic Product Color Scheme Using Parametric Color Images with Analysis〔碩士論文，國立臺灣師範大學〕。華藝線上圖書館。https://doi.org/10.6345/NTNU201901174