An expert system for general symbol recognition

✍ Scribed by Maher Ahmed; Rabab Kreidieh Ward

• Book ID: 104160538
• Publisher: Elsevier Science
• Year: 2000
• Tongue: English
• Weight: 497 KB
• Volume: 33
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(99)00191-0

✦ Synopsis

An expert system for analysis and recognition of general symbols is introduced. The system uses the structural pattern recognition technique for modeling symbols by a set of straight lines referred to as segments. The system rotates, scales and thins the symbol, then extracts the symbol strokes. Each stroke is transferred into segments (straight lines). The system is shown to be able to map similar styles of the symbol to the same representation. When the system had some stored models for each symbol (an average of 97 models/symbol), the rejection rate was 16.1% and the recognition rate was 83.9% of which 95% was recognized correctly. The system is tested by 5726 handwritten characters from the Center of Excellence for Document Analysis and Recognition (CEDAR) database. The system is capable of learning new symbols by simply adding their models to the system knowledge base.