Title :
Knowledge-based hierarchical sketch understanding
Author :
Zheng, Wen-Tao ; SUN, ZHENG-XING
Author_Institution :
State Key Lab for Novel Software Technol., Nanjing Univ., China
Abstract :
This article presents a knowledge-based framework for sketch understanding. Compared to traditional sketch understanding systems, it has two significant features: (1) knowledge-based. This makes the system independent of applied domain. Users can easily design an ontology-based domain knowledge base to guide the understanding process. (2) hierarchical approach. The sketch understanding process is divided into three phases: token recognition, salient symbol recognition and integral recognition. During all these phases, domain knowledge is used as a guider. In addition, a domain knowledge base of UML class diagram is presented as a case study of this framework, in which the details of how to design ontology-based knowledge base and how to implement a hierarchical recognition are given. Some UML class diagram sketches are used as experiments, which produce satisfactory results.
Keywords :
Unified Modeling Language; handwriting recognition; knowledge based systems; ontologies (artificial intelligence); UML class diagram; hierarchical recognition; integral recognition; knowledge-based hierarchical sketch understanding; ontology-based domain knowledge base; salient symbol recognition; token recognition; Automatic speech recognition; Handwriting recognition; Hardware; Learning systems; Ontologies; Shape; Speech recognition; Sun; Unified modeling language; User interfaces; Knowledge base; Sketch understanding; ontology;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527426