Locating pattern groups in segmented color images

Finding useful information in real world scenes is very important for many scene-understanding tasks. Signs, scripts, information panels, and logos typically stand out from their environment for a human observer, but locating them algorithmically seems to depend on the actual context. We propose a hierarchical method that locates interesting pattern groups on segmented color images by creating a layered structure based on neighborhood topography and applying the Gestalt principles. The proposed algorithm can be efficiently implemented on processor arrays, since it mostly contains standard topographic instructions. A comparative analysis with a similar binary technique through several examples is included.