Spectral and Spatial Invariant Image Retrieval using Scene Structural Matrix

We introduce Scene Structural Matrix (SSM), a novel image content descriptor and its application to invariant image retrieval. The SSM captures the overall structural characteristics of the scene by indexing the geometric features of the image. We employ a binary image tree (bintree) to partition the image and from which we derive multiscale geometric structural descriptors of the image. We have applied the SSM to contentbased image retrieval from image databases. Experimental results show that SSM is particularly effective in retrieving images with strong structural features, such as landscape photographs. We will show that SSM is robust against spatial and spectral distortions thus making it superior to current state of the art techniques such as colour correlogram in certain applications. We will also show that images retrieved by the SSM are more relevant than those returned by colour correlogram and colour histogram.