A method for measuring the complexity of image databases

We present a framework for measuring the complexity of image databases, which characterizes the databases for image retrieval. Motivated from the concept of text corpus perplexity, the complexity of image databases is formulated based on image database statistics and information theory. We propose a quantitative metric which can be used to measure the degree of difficulty to retrieve images based on contents of the database. This metric is independent of queries, hence, it is objective. Experiments on both synthetic and real-world images demonstrate that the proposed measurement is highly effective in quantitatively measuring the contents of image databases for content-based retrieval.