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价方法。研究涉及：（1）测量图像测试床的复杂度，其可以用于定量地确定从图像测试床检索图像的困难程度，以及（2）比较不同检索方法的性能，其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一般框架，可用作对图像进行统计分析的工具，并为建立评估方法奠定了基础。使用这个框架，评价方法可以衡量其交叉熵的图像数据库的复杂性和排序的检索方法，其交叉熵相对于一个特定的测试床。因此，图像测试床可以在支持图像查询的复杂性上相互比较。此外，检索技术可以相互比较，而无需使用查询，从而避免了人类的主观性。本计画所开发之演算法将为社群提供宝贵的财富，以最终建立一套一般性的基于内容的影像撷取研究评估方法论理论。

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.