RFLPRetriever: A content-based retrieval system for biological image databases

The reliance of life science researchers on computer systems has increased dramatically with the progress of the various genome projects. Currently, the demand exists for a biological image database system for the storage and retrieval of RFLP (Restriction Fragment Length Polymorphism) images. To fulfill this need, we have developed a content-based image retrieval (CBIR) system - RFLPRetriever - for the biological research community. Implementing a CBIR system for storage and retrieval of RFLP images provides several advantages. For example, when a biologist clones a gene, he or she must discover whether the gene has previously been cloned. To do this, the researcher needs to look through thousands of images in search of an RFLP image that contains a similar set of biologically meaningful features as a related image created in the lab. One advantage of using a CBIR system is that by taking the extracted feature vectors, an efficient database indexing structure can be created, providing the system with a rapid retrieval rate. In addition, a CBIR system allows the user to search an image database by submitting a query image in which the user wants to find a matching RFLP image based on a combination of biologically relevant attributes contained in the query image.