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...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.展开更多
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 i...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.展开更多
基金This paper has been supported by the National Natural Science Foundation of China (Grant No. 61371040).
文摘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.
文摘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.
