感兴趣区域的确定及相似度计算方法

Methods on ROI Confirmed and Similarity Computation

对ROIBIR系统中ROI的确定及区域相似度计算进行了研究。首先介绍了两种确定ROI的方法,它们充分利用分割区域的用户可见性、区域及其权重用户的可指定性来实现用户的可选性,使图像的检索系统融合人的感知能力,符合人们的检索习惯。然后介绍了一种基于区域的图像相似度计算方法,这种方法先分别按照区域的综合特征、直方图特征值及区域的形状特征进行相似度计算,再将各自相似度加权乘积作为两区域的相似度,各区域最大相似度的平均值作为感兴趣区域与目标图像的相似度。并用实验证明了提出方法的有效性。

The key techniques on ROI confirmed and similarity computation in ROIBIR system are studied. Firstly, two approaches of confirming ROI are introduced by considering the visibility of image regions, the possibility of designating region and its weight for users making the image retrieval system include human perception and accord with human vision habits. Then, a region-based similarity measurement approach is introduced. With the proposed approach, the similarity of two regions with the combination features, histogram and region shape features is computed respectively. Then, the similarity of two regions is computed by the weight product method. The average value＇s similarity for every region is regarded as the similarity of ROI and target image. Experiments show that the proposed methods are available.