基于k-Means算法的泰米尔语手写词识别

Aravinda C.V, N. PrakashH.
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引用次数: 0

摘要

尽管如此,随着泰米尔文字的进步,书写仍然是日常生活中报告信息的一种策略。划分和肯定位置的方法消除了大量的麻烦,特别是在看到不同语言的草书物理组成的文字。这是为了在印度、斯里兰卡、新加坡等国的官方语言——泰米尔语中,对手写文字进行泰米尔文字确认而提出的回答。该方法利用KNN算法技术来识别草书解密泰米尔字符。结构的冲突是显而易见的,因为它可以压倒从内容样式分类中发展出来的复杂性,并最终成为多功能和坚实的。在扫描数据库上使用该方法获得了更高的结果精度,并且结果的精度显示了其在业务使用中的应用。方法论认证展示了一个必要的和轻快的系统,以创建一个完整的OCR结构,并与明智的预准备相连接。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tamil HandWritten Word Recognition with Entrenched Attributes using k-Means Algorithm
In spite, couple types of progress in advancements identifying with Tamil Optical character affirmation, handwriting continues hanging on as strategy for reporting information for ordinary life. The methodology of division and affirmation positions quiets a huge amount of troubles especially in seeing cursive physically composed scripts of different lingos. The thought proposed is an answer made to perform tamil character affirmation of composed by hand scripts in Tamil, a language having official status in India, Sri Lanka, and Singapore. The approach utilizes KNN Algorithm technique for seeing charted off cursive decrypted Tamil characters. The conflict of the structure is obvious as it can overwhelm the complexities develop out of content style assortments and winds up being versatile and solid. More elevated amount of precision in results has been obtained with the use of this procedure on a sweeping database and the precision of the results displays its application on business use. The methodology certifications to demonstrate an essential and brisk system to create a full OCR structure connected with sensible pre-get ready.
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