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标题：Handwritten Character Recognition Mistreatment Multiclass SVM Classification with Hybrid Feature Extraction
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作者：A.Rama ; B.Nagalakshmi
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：11
出版社：S&S Publications
摘要：In this paper, we tend to describe hybrid feature extraction for offline written character recognition. Theprojected technique could be a hybrid of structural, applied math and correlation options. within the opening, theprojected technique identifies the kind and placement of some elementary strokes within the character. The strokes tobe hunted for comprise horizontal, vertical, positive slant and negative slant lines–as we tend to observe that thestructure of any character are often approximated with the assistance of a mix of straightforward line strokes. Thestrokes ar known by correlating completely different segments of the character with the chosen elementary shapes.These normalized correlation values at completely different segments of the character offer correlation options. forcreating feature extraction additional strong, we tend to add within the second step sure structural/statistical options tothe correlation options. The additional structural/statistical options ar supported projections, profiles, invariantmoments, endpoints and junction points. This increased, powerful combination of options leads to a 157-variablefeature vector for every character, that we discover adequate enough to unambiguously represent and determine everycharacter. Prior, written character recognition downside has not been self-addressed the means our projected hybridfeature extraction technique deals with it. The extracted feature vector is employed throughout the coaching section forbuilding a support vector machine (SVM) classifier. Thetrained SVM classifier is after used throughout the testingsection for classifying unknown characters. Experiments were performed on written digit characters and uppercasealphabets taken from completely different writers, with none constraint on style. The obtained results were comparedwith some connected existing approaches. attributable to the projected technique, the results obtained show higherpotency concerning classifier accuracy, memory size and coaching time as compared to those different existingapproaches.
关键词：character recognition; feature extraction; correlation perform; SVM