文章基本信息

标题：Non-Linear Segmentation of Touched Roman Characters Based on Genetic Algorithm
本地全文：下载
作者：Tanzila Saba ; Ghazali Sulong ; Amjad Rehman 等
期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2010
卷号：2
期号：6
页码：2167-2172
出版社：Engg Journals Publications
摘要：The segmentation accuracy of Roman cursive characters, especially touched characters, is essential for the high performance of Optical Character Recognition Systems. This paper presents a new approach for non-linear segmentation of multiple touched Roman cursive characters based on genetic algorithm. Initially, a possible segmentation zone is detected and then best segmentation path is evolved by genetic algorithm. The initial population is composed of each point column in possible segmentation zone. The individual coding, fitness function, crossover operator and mutation operator are also defined for this task. Experimental results on a test set extracted on the IAM benchmark database exhibit high segmentation accuracy up to 89.76%. Proposed approach can handle some complex types of touched cursive characters without special heuristic rules and recognition.
关键词：-