A Color Image Retrieval Method Based on Improved Blocked Color Histograms and Fuzzy C-means Clustering
Gaofeng Xu · Computer Engineering and Science · 2011
The application of data mining clustering algorithms in content-based image retrieval can effectively optimize the retrieval speed and effect,to be more specific,fuzzy clustering algorithms fit better the fuzzy characteristics of image retrieval,but affect the retrieval function with a long clustering time,so a color image retrieval method based on improved blocked color histograms and fuzzy c-means clustering is proposed.First,each image in the image library is blocked,the improved color characteristic information of each block is extracted;a fuzzy c-means clustering algorithm is used to cluster color feature vectors,and each cluster center of image class is obtained;finally,the similarity between the sample image and the corresponding categories is calculated,returning the retrieval results according to the size of similarity.The experiments show that the proposed method has a higher recall rate and a higher precision rate,and less feature dimension of extraction,a shorter clustering time and a quicker retrieval speed.