Bimodal system for interactive indexing and retrieval of pathology images
We demonstrate the prototype of an image understanding based system to support decision making in clinical pathology. The system employs all four major low level vision queues (shape, texture, color, metric measures) in content-based retrieval of visual information. The reliability of the central module of the system, the fast color segmenter, makes possible on-line analysis of the query image. The user interface is bimodal (speech and mouse input), allowing a natural communication with the system.