Measuring Performance of Web Image Context Extraction

摘要

Images on the Web appear with textual contents providing meaningful information to their semantics. Methods that automatically determine and extract the Web image context from an HTML document are widely used in different applications. However, the performance of the image context extraction has rather been evaluated on its own. Keeping this imperative in mind, we present a framework to objective evaluation and comparison of the performance of image context extraction methods. This is achieved by collecting a large ground truth dataset consisting of diverse Web documents from real Web servers and by defining performance measures adapted to fit the special properties of the context extraction task. To show the capabilities of the proposed framework, common extraction methods from the literature have been evaluated and the results are summarized in this paper.