Online Visualisation of Google Images Results

Abstract

Visual information, especially in the form of images, is becoming increasingly important, and consequently there is a rising demand for effective tools to perform online image search. However, image search engines such as Google Images, are based on the text surrounding the images rather than the images themselves. At the same time, while the employed keyword-based search provides a basic level of filtering, it is not sufficient to handle large search results. Image database visualisation, which provides a visual overview of an image collection, could be applied to the retrieved images, but the associated overheads, both in terms of bandwidth and computational complexity, are prohibitive. In this paper, we introduce an image browsing system that does not suffer from these drawbacks. In particular, we construct an interactive image database navigation application that uses the Huffman tables available in the JPEG headers of Google Images thumbnails directly as image features, and projects images onto a 2-dimensional visualisation space based on principal component analysis derived from the Huffman entries. Images are dynamically placed into a grid structure and organised in a tree-like hierarchy for visual browsing. Since we utilise information only from the JPEG header, the requirement in terms of bandwidth is very low, while no explicit feature calculation needs to be performed, thus allowing for interactive browsing of online image search results.