基于改进距离聚合向量的图像检索算法

An Improved Distance Coherence Vector Algorithm for CBIR

针对Sajjanhar等提出的基于距离聚合向量的图像检索算法的不足,提出一种改进距离聚合向量的图像检索算法.该算法在距离聚合向量的基础上加入最大连通聚合像素平均坐标的质心距离特征,新增的特征向量具有平移、旋转和尺度不变性.对于原聚合向量特征和新增的质心距离特征,分别采用不同的相似性度量函数进行相似度匹配.该改进算法融入比距离聚合向量更多的空间信息.实验结果表明,该算法具有更高的查全率和准确率.

An improved distance coherence vector for content-based image retrieval （CBIR） is proposed to improve the algorithm proposed by Sajjanhar et al. The improved algorithm regards centroidal distances vector of average coordinates from the biggest eonnected coherence pixels as a new feature vector. The new added feature vector is invariable to translation, measured by different similar functions according better retrieval effect due to the more introduced scaling and rotation. Similarity of images is to different feature vectors. spatial that the improved algorithm has high recall and precision. The improved algorithm has information. The experimental results indicate