Cvus: A Computer Vision-understanding System
This paper presents a Lisp-based system for understanding the computer vision (CVUS). The system is basicly composed of four parts: Knowledge Base (KB), Image-Under- standing Modules (IUM), Image Data Base (IDB) and a Master Control Program (MCP). There are two kinds of knowledge in the KB, rules and frames. The rule includes the declarative rule and the image rule. The frame is an object knowledge code. There are two kinds of frames in the system: the concept frame and the rule frame. The concept frame is used for representing a basic vision concept. The rule frame is used for representing the relative rules. The IUM is mainly composed of two parts: image precessing and reasoning. The main purpose of the image processing is to identify the sense elements and set up their relationship. The inference mechanism uses backward chaining control strategy and the inference model adopts the inexactly reasoning model. There are four kinds of image data in the IDB. They are original vision image data, labeled image data, basic elements data and logical relationship data. The relation model is adopted to organize the data. The MCP coordinates the different parts in the system,,establishes the synchronization and chooses at appropriate processing model to perform the suitable computer vision- understanding procedure.