Efficient color image indexing and retrieval using a vector-based scheme

Color is the characteristic which is most used for image indexing and retrieval. Due to its simplicity, the color histogram remains the most commonly used method for color indexing and retrieval. However, the lack of good perceptual histogram similarity measures, the global color content of histograms and the erroneous retrieval results due to gamma nonlinearity, calls for improved methods. We implement a vector angular-based distance measure for image retrieval based on color. We build distance vectors in a multidimensional query space in which the retrieval ranking of each image is determined. Our system exhibits high flexibility by allowing all types of queries, including query by color, query by multiple colors and query by example. In addition, colors can be excluded in a query, without requiring an additional level of analysis.