期刊名称：International Journal of Advanced Computer Research
印刷版ISSN：2249-7277
电子版ISSN：2277-7970
出版年度：2011
卷号：2011
出版社：Association of Computer Communication Education for National Triumph (ACCENT)
摘要：A system has been developed for text writing systems using Support Vector Machines (SVM) is called Handwritten Character Recognition (HCR). The main challenge in handwritten character recognition for Small and Capital letter is to build a system that is able to distinguish between variation in writing the same stroke (when the same stroke is written by different writers or the same writer at different times) and minor variation in similar characters in the script. Other issues faced can be attributed to the large number of character and stroke classes. Some Indian scripts have character modifiers occurring in multiple non-overlapping horizontal units which are positioned on one or both sides of the main consonant. In such cases, we may also need to keep track of the sequence of horizontal units as they are written. The main problem in handwritten character recognition is recognition for Small and Capital letter is to build a system that is able to distinguish between variation in writing the same stroke and minor variation in similar characters in the script. Handwritten character recognition is not a new technology but it not gained public attention. The various features that are considered for classification are the character height, character width, the number of horizontal lines (long and short, image centroid and special dots. In this research paper extracted features were passed to a Support Vector Machine (SVM) where the characters are classified by Supervised Learning Algorithm. These classes are mapped onto for recognition. Then the text is reconstructed using fonts
关键词：OCR; Features; Support Vector Machine (SVM); ;Artificial Neural Networks; Handwritten Character ;Recognition; Stroke; Printed Characters
