Research on Feature Fusion Technology of Fruit and Vegetable Image Recognition Based on SVM

• 作者: Chaoxia Shi Hui Shi Yanqing Wang Yipu Wang
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: FEATURE extraction Multi-feature FUSION Support VECTOR machine FRUIT and VEGETABLE image RECOGNITION
• 年，卷（期）: 2016,（1）
• 页码范围: 150-152
• 页数: 3页
• 分类号: C5

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.