Chen Jing, Zhu Qibing, Huang Min, Zheng Yang. Recognition of Empoasca Flavescens Based on Machine Vision[J]. Laser & Optoelectronics Progress, 2018, 55(1): 11502
- Laser & Optoelectronics Progress
- Vol. 55, Issue 1, 11502 (2018)
Fig. 1. Partial experimental pictures
Fig. 2. Box-plot of color features for Empoasca flavescens and other insects
Fig. 3. Process of Empoasca flavescens recognition
Fig. 4. Segmentation results using different algorithms. (a) Original image; (b) traditional Ostu algorithm; (c) K_means clustering algorithm
Fig. 5. DBSCAN clustering results. (a) Setting threshold to 8; (b) setting threshold to 12; (c) clustering fusion result
Fig. 6. Accuracy versus number of selecting samples for different algorithms. (a) KS algorithm; (b) random selection
Fig. 7. Partial recognition results. (a) Correct recognition; (b) misrecognition; (c) leakage recognition
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Table 1. Number of Empoasca flavescens separated by different algorithms
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Table 2. The test accuracy obtained by different training methods%
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