A hybrid algorithm based on improved LLE and k-means for visual codebook generation in scene classification

Abstract

This paper proposes a hybrid algorithm based on improved LLE and adaptive k-means for visual codebook generation in tourism scene classification. Firstly, we construct the improved LLE algorithm to get lower dimensional and compressed image feature representations. Then we form the adaptive k-means clustering algorithm to generate the visual codebook. Finally, we use the visual codebook histogram to represent the samples and train the SVM classifier for scene classification task. Experiments are conducted on a Beijing tourism scene dataset to evaluate the performance of the hybrid algorithm. Experimental results show that our algorithm can effectively improve the robustness of the visual codebook and result in a satisfying performance of scene classification.