With the rapid development of the Internet, finding desired images from numerous images has become an important research topic. In this paper, we propose an image retrieval system facilitating retrieval time and accuracy. Since the performance of image retrieval is deeply influenced by image features and retrieval methods. Five different types of features and five different methods are used to find the best combination for an image retrieval system. First, we segment out the main object in an image and then extract its features. Next, relevant features are selected from the original feature set for facilitating image retrieval, using the SAHS algorithm. Then, five methods based on AND/OR-construction are proposed to build the image retrieval model, using the relevant features. Finally, the experimental results not only show that our methods are more effective than the other state-of-the-art methods but also present some observations never explored by the previous research.

随着互联网的快速发展，从众多图像中寻找所需图像已经成为重要的研究课题。在本文中，我们提出了一种便于检索时间和准确性的图像检索系统。由于图像检索的性能深受图像特征和检索方法的影响。使用五种不同类型的功能和五种不同方法来找到图像检索系统的最佳组合。首先，我们在图像中分割出主要对象，然后提取其特征。接下来，使用SAHS算法从原始特征集中选择相关特征以促进图像检索。然后，提出了五种基于与/或构造的方法，利用相关特征建立图像检索模型。最后，