Research on Technology of Twin Image Recognition Based on the Multi-feature Fusion

摘要

In order to improve the accuracy and stability of fruit and vegetable image recognition by single feature,this project proposed multi-feature fusion algorithms and SVM classification algorithms.This project not only introduces the Reproducing Kernel Hilbert space to improve the multi-feature compatibility and improve multi-feature fusion algorithm,but also introduces TPS transformation model in SVM classifier to improve the classification accuracy,real-time and robustness of integration feature.By using multi-feature fusion algorithms and SVM classification algorithms,experimental results show that we can recognize the common fruit and vegetable images efficiently and accurately.