Prototyping structural description using an inductive learning program

作     者：Amin, A 

作者机构：Univ New S Wales Sch Comp Sci Sydney NSW 2052 Australia 

出 版 物：《IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS》 (IEEE Trans Syst Man Cybern Pt C Appl Rev)

年 卷 期：2000年第30卷第1期

页      面：150-157页

核心收录：

主　　题：Arabic characters feature extraction hand-printed characters inductive logic programming parallel thinning pattern recognition structural classification 

摘      要：Character recognition systems can contribute tremendously to the advancement of the automation process and can improve the interaction between man and machine in many applications, including office automation, check verification and a large variety of banking, business and data entry applications. The main theme of this paper is the automatic recognition of hand printed Arabic characters using machine learning. Conventional methods have relied on hand-constructed dictionaries which are tedious to construct and difficult to make tolerant to variation in writing styles. The advantages of machine learning are that it can generalize over the large degree of variation between writing styles and recognition rules can be constructed by example. The system was tested on a sample of handwritten characters from several individuals whose writing ranged from acceptable to poor in quality and the correct average recognition rate obtained using cross-validation was 89.65%.