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Handwritten Marathi Compound Character Segmentation Using Minutiae Detection Algorithm

机译:使用细节检测算法的手写Marathi复合字符分割

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Segmentation process is the heart of handwritten Script Identification system. Aside from the large variation of individual's handwriting, many researchersfound difficulty to separate characters from scanned word document Image. The key factor of selection of segmentation algorithm is used to improve efficiency of character segmentation as well as good feature extraction. One of the feature of Marathi script is Compound Character, derived from Devnagari, occur rarely in the script. Segmentation of such type characters is very difficult due to their complex structure. This paper proposed new technique for segmentation of handwritten Marathi compound characters. The Proposed algorithm used the concept of Minutiae extraction for fingerprint for segmenting the compound character. Basically Segmentation is carried out using morphological operations such as erosion and dilation. For segmenting the character from compound character our aim to find termination point and bifurcation points. And for finding the termination and bifurcation point proposed algorithm used the morphological operation hit or miss transform. The experimentalresults shows 90% accuracy in finding termination and bifurcation points.
机译:分割过程是手写脚本识别系统的核心。除了个人笔迹的巨大差异外,许多研究人员还发现很难从扫描的单词文档图像中分离字符。选择分割算法的关键因素是提高字符分割效率以及良好的特征提取。 Marathi脚本的功能之一是源自Devnagari的Composite Character,在脚本中很少出现。由于其复杂的结构,很难对这类字符进行分割。本文提出了一种新的手写Marathi复合字符分割技术。提出的算法使用Minutiae提取的概念来指纹,以分割复合字符。基本上,分割是使用形态学操作(例如腐蚀和膨胀)进行的。为了从复合字符中分割字符,我们的目的是找到终止点和分支点。为了找到终止点和分叉点,提出的算法使用形态学运算命中或未命中变换。实验结果表明,找到终止点和分叉点的准确性为90%。

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