文章基本信息

标题：Handwritten Gurmukhi Character Recognition Using Statistical and Background Directional Distribution Features
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作者：Kartar Singh Siddharth ; Mahesh Jangid ; Renu Dhir 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：2011
卷号：3
期号：6
页码：2332-2345
出版社：Engg Journals Publications
摘要：In this manuscript handwritten Gurmukhi character recognition for isolated characters is proposed. We have used some statistical features like zonal density, projection histograms (horizontal, vertical and both diagonal), distance profiles (from left, right, top and bottom sides). In addition, we have used background directional distribution (BDD) features. Our database consists of 200 samples of each of basic 35 characters of Gurmukhi script collected from different writers. These samples are pre-processed and normalized to 32*32 sizes. SVM, K-NN and PNN classifiers are used for classification. The performance comparison of features used in different combination with different classifiers is presented and analysed. The highest accuracy obtained is 95.04% as 5-fold cross validation of whole database using zonal density and background distribution features in combination with SVM classifier used with RBF kernel.
关键词：isolated handwritten Gurmukhi character recognition; statistical features; zoning; density; projection histogram; distance profile; background directional distribution; SVM; K-NN; PNN; RBF kernel