Evaluation Methodology for Image Testbed and Content-Based Retrieval

该项目旨在开发一种基于内容的图像检索的评估方法。研究内容包括：(1)图像测试床复杂度的测量，它可以定量地确定从图像测试床上检索图像的难度程度；(2)不同检索方法的性能比较，可以定量地给出检索方法的性能的客观排名。该项目设计了一个图像特征表示的总体框架，可作为对图像进行统计分析的工具，并为建立评价方法奠定了基础。使用该框架，该评价方法可以通过图像数据库的交叉熵来衡量其复杂性，并根据它们相对于特定测试床的交叉熵来对检索方法进行排序。因此，可以将图像试验台在支持图像查询方面的复杂性相互比较。此外，这些检索技术可以在不使用查询的情况下进行相互比较，从而避免了人为的主观性。该项目中开发的算法将是社区最终建立基于内容的图像检索研究的评估方法的一般理论的宝贵财富。

The project aims at developing an evaluation methodology for content-based image retrieval. The research involves: (1) Measurement of the complexity of image testbeds which can be used to quantitatively determine the degree of difficulty in retrieving images from the image testbeds, and (2) Comparison of the performance of different retrieval approaches which can quantitatively give an objective ranking of the performance of the retrieval approaches. The project designs a general framework of image feature representations which can be used as a vehicle to conduct statistical analysis on images and forms a basis for establishing the evaluation methodology. Using this framework,the evaluation method can measure the complexity of the image databases by their cross entropy and rank the retrieval approaches by their cross entropy with respect to a particular testbed. The image testbeds can thus be compared with each other on their complexity in supporting image querying. Furthermore, the retrieval techniques can be compared with each other without using queries so the human subjectivity is avoided. The algorithms developed in this project will be a valuable asset for the community to eventually establish a general theory of the evaluation methodology for content-based image retrieval research.