一种基于用户感兴趣区域的图像检索算法

利用图像全局特征的检索不能很好地检索用户想要的对象内容,而基于分割后各区域特征的检索又过分依赖于复杂的图像分割算法。针对上述两者的缺点,文中提出了一种基于用户感兴趣区域的图像检索算法。该算法首先对样例进行多分辨率树状分解,再由用户选择分解后的任意多个感兴趣的子图,提取子图的特征以进行相似性度量,并应用相关反馈以更好地捕获用户的检索意图。该方法无需对图像进行复杂的分割就能提取对象特征,且经由实验证明具有较高的查全率。

An Image Retrieval Algorithm Based on Region of Interest

Image retrieval using the feature of the entire image neglects the objects in which the user is interested,while the result of segmented regions-based retrieval excessively depends on complicated segmentation algorithm.An image retrieval algorithm based on region-of-interest is proposed in this paper aiming at covering those two shortages.This algorithm firstly decomposes the sample image into sub-images by multiresolution tree,and then the feature of the sub-images of interest selected by the user is extracted for similarity measure.We also investigate the use of feedback to better capture the user's intention.This approach can extract the feature of object without segmentation,and our experiments show that it can achieve high rate of recall.