Flower Image Retrieval Based on Multi-features Fusion
基于多特征融合的花卉图像检索

This paper had systematic and overall researches on flower images, including regional segmentation, feature extraction, content based duplicate images filtering and SVM-based image retrieval, etc. Firstly, in order to ensure retrieval results, we proposed duplicate images filtering algorithm based on Canny edge to detect duplicate images. Then we proposed adaptive threshold segmentation algorithm based on 2RGB mixed color model to segment flower images.Using multi-feature fusion strategy for feature extraction, we proposed weighted invariant moment shape based on HSV color model, as well as edge LBP feature which both combined texture feature and shape feature. Finally, we executed experiments on flower image library, comparative results show that above algorithms are effective.