Abstract

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%.

Keywords:

Fruit color recognition, multiple classifier combination, support vector machine,

References

1. Dimitrakopoulos, G. and P. Demestichas, 2010. Intelligent food systems [J]. IEEE Vehic. Technol. Magaz., 5(1): 77-84.
   
2. Janowski, L., P. KozPwski and R. Baran, 2014. Quality assessment for a visual and automatic species plate recognition [J]. Multimedia Tools Appl., 68(1): 23-40.
   CrossRef    
3. Jing, N., 2007. Research on Several Important Algorithms in Color Recognition of Fruit-Body [D]. Shenyang University of Technology, Shenyang, 2007.
   
4. Lee, R.C., K.C. Hung and H.S. Wang, 2013. Real-time fruit species plate recognition based on scanning and 2D haar discrete wavelet transform [J]. Appl. Mech. Mater., 284: 2402-2406.
   
5. Li, G.J., Z.X. Liu, Z.S. You and et al., 2004. Fruit-body color recognition algorithm based on color difference and color normalization [J]. Comput. Appl., 24(9): 47-49.
   
6. Peng, Y., J.S. Jin and S. Luo, 2012. Fruit type classification using pca with self-clustering [C]. Proceeding of IEEE International Conference on Multimedia and Expo Workshops (ICMEW), pp: 384-389.
   PMid:21856370    

Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.