一种基于图像显著特征点的检索算法

Image Retrieval Algorithm Based on Salient Points

提出一种基于图像显著特征点的检索算法.首先给出一种具有一定自适应能力的显著特征点的提取算法,即采用改进的图像的块逆概率差模型来提取原图像的块逆概率差图像(DBIP 图像).在此基础上,根据 BDIP 图像中像素的分布特点来提取图像的显著特征点.然后以它们为线索,把图像的形状特征和空间颜色分布特征有机结合起来进行检索.该算法不仅克服利用兴趣点检索时的缺点,而且降低传统显著点提取算法的复杂度,又包含一定的形状信息,具有较好的检索效率.实验结果表明,该算法是有效的.

An image retrieval algorithm based on salient points is proposed. Firstly, a robust and self- adaptive extraction algorithm of salient points is introduced based on the block difference of inverse probabilities model image which was built by an improved block difference of inverse probabilities model. According to the distribution of salient points, the color-spatial feature and the shape feature are extracted to represent image properties for retrieval. The algorithm avoids the defects of interest points in the image retrieval. Furthermore, it reduces the computational complexity of traditional extraction algorithm of salient points. The experimental results demonstrate the proposed method has better performance and higher accuracy than other algorithms.