Kernels in structured multi-feature spaces for image retrieval
A new kernel for structured multi-feature spaces is introduced. It exploits the diversity of information encapsulated in different features. The mathematical validity of the introduced kernel is proven in the context of a conventional convex optimisation problem for support vector machines. Computer simulations show high performance for classification of images.