Apple NIR Spectral Classification Method
Min Li, Jin Cao, Linju Lu
Available Online June 2015.
- https://doi.org/10.2991/icecee-15.2015.38How to use a DOI?
- Apple; Near Infrared Spectroscopy; Principal Component Analysis; Fisher Decision Analysis; K- Nearest Neighbor Classification
- This paper proposed an apple near infrared spectral classification method. Red Fuji apples from Shandong and Shaanxi province , “Huaniu” apples from Gansu province were used as experimental materials. NIR data of three kinds of apples after preprocessing by wavelet soft threshold, was removed the noise and redundancy. Then the method of Principal Component Analysis ( PCA) was used to reduce the dimension, and the Fisher Decision Analysis (FDA) was used for further feature extraction. Finally the K-Nearest Neighbor (KNN) classification was run, and K = 4. Through the experimental comparison, the method can achieve good feature extraction and classification of apples. The correct identification rate reaches above 96%. This method can realize different kinds of apples nondestructively, rapidly and accurately, which provides a new idea for near infrared spectral analysis technology.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Min Li AU - Jin Cao AU - Linju Lu PY - 2015/06 DA - 2015/06 TI - Apple NIR Spectral Classification Method BT - 2015 2nd International Conference on Electrical, Computer Engineering and Electronics PB - Atlantis Press SP - 168 EP - 171 SN - 2352-538X UR - https://doi.org/10.2991/icecee-15.2015.38 DO - https://doi.org/10.2991/icecee-15.2015.38 ID - Li2015/06 ER -