基于颜色和形状特征的彩色图像显示与检索技术

提出了一种有效用于抽取特征、索引和检索彩色图像的技术途径，通过提取图像的颜色不变量，建立相应的色度直方图（hue histogram）来表示图像的颜色分布特征，为了描述图像中对象的位置及方向特征，首先计算图像的色度轮廓并对其进行Radon变换，然后计算相应的“空间直方图”，由此，得到了一种基于图像的颜色分布特征和形状特征的新的图像表示方法，为了计量图像的全局相似度，基于“累积距离”和“基于向量的距离”定义了两种图像的距离度量，并分别讨论了距离度量的选取与归一化、不同子特征的组合等CBIR所涉及的关键问题，实验结果表明，文中提出的方法能获得满意的检索性能，其检索结果能较好地接近于人的视觉感和结果。

Color and Shape Based Image Representation and Retrieval

A novel and efficient scheme for feature extracting, indexing, and retrieving color image is presented. To extract color feature, a simple invariant labeling function is defined to measure the hue of each pixel, and hue histogram is generated which represents the distribution of hue values in an image. To describe the relative position and orientation of objects within the image, hue edges in the image, computed using Canny approach, are processed by Radon transformation to generate the spatial histogram which is used as shape representation. To address the issue of image matching, we define two global distance measures based on the accumulative distance and vector based distance to compare the similarity of two images. In addition, some key problems such as the combination of different subfeatures and normalization of distance measures are also discussed in detail. Experimental results indicate that our approach provides perceptually appealing results and high retrieval rate.