Vector Space Image Model (VSIM) for Content-Based Image Retrieval

A new method for content-based image retrieval is being presented. This method uses a vector-space model to represent images in a multi-dimensional space. This model allows the use of multiple attributes in the retrieval process and also identiies the most selective values for each attribute. Therefore by ignoring the less signiicant values the user can reduce the dimensionality of the feature set and simplify the vector model. It also allows the user to choose any similarity measure depending on the application. The user can also assign weights to the diierent attributes depending on the retrieval mechanism intended. These characteristics of the retrieval method increase the retrieval eeciency and makes the model very exible as it can be used universally for retrieving images from different domains.