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Isolated Handwritten Malayalam Character Recognition Using HLH Intensity Patterns

机译:使用HLH强度样式的隔绝了手写的马拉塔拉姆字符识别

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Recently Indian Handwritten character recognition is getting much more attention and researchers are contributing a lot in this field. But Malayalam, a South Indian language has very less works in this area and needs further attention. This paper focuses on an efficient algorithm for recognizing the handwritten Malayalam characters. Malayalam OCR is a complex task owing to the various character scripts available and more importantly the difference in ways in which the characters are written. The dimensions are never the same and may be never mapped on to a square grid unlike English characters. Here we propose an algorithm which can accept the scanned image of handwritten characters as input and to produce the editable Malayalam characters in a predefined format as output without applying any resizing or skeletonization methods but still can produce much accurate results. Characters are grouped in to different classes based on their HLH intensity patterns. These patterns are separated from the image and fed for recognition. Algorithm is tested for 4 sets of samples ranging 661 letters in the noiseless environment and produces an accuracy of 88%.
机译:最近,印度手写的性格识别正在得到更多的关注,研究人员在这一领域贡献了很多。但是马拉雅拉姆,南印度语言在这一领域的作品非常少,需要进一步关注。本文侧重于识别手写的Malayalam字符的有效算法。 Malayalam OCR是由于各种字符脚本可用的复杂任务,更重要的是,写入字符的方式的差异。与英语字符不同,尺寸永远不会相同,并且可能永远不会映射到正方形网格。在这里,我们提出了一种算法,它可以接受手写字符的扫描图像作为输入,并以预定义的格式生成可编辑的MALAYALAM字符作为输出而不应用任何调整大小或骨架化方法,但仍然可以产生大量准确的结果。基于其HLH强度模式,字符被分组到不同的类别。这些模式与图像分离并供给识别。测试算法4套样本在无噪声环境中测距661个字母,并产生88&#x025的准确性;

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