in this paper we study the feasibility of developing a search engine capable of retrieving images from a granite image database based on a query image that is similar to the intended targets. the main focus was on the determination of the set of colour and/or texture features which yields highest retrieval accuracy. to assess the performance of the considered image descriptors we created a granite image database, formed by images recorded at our laboratory as well as taken from the internet. experimental results show that colour and texture features can be successfully employed to retrieve granite images from a database. we also found that improved accuracy is achieved by combining different colour and texture feature sets through classifier fusion schemes.