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Studi Analisis Pengenalan Pola Tulisan Tangan Angka Arabic (Indian) Menggunakan Metode K- Nearest Neighbors dan Connected Component Labeling

机译:阿拉伯语(印度)数字的手写识别模式的K最近邻法和连接组件标注方法的分析研究

摘要

Handwriting refers to the result of writing by hand (not typed). The writing style of people are not the same. One of the United Nations official languages, Arabic, has a numerical system known as Arabic (Indian) numeral. The identification of feature help humans to be able distinguish the patterns. The grouping patterns can be applied to the machine for recognizing object in the image. Connected component labeling is used for separating characters to be easily recognizable. K- nearest neighbors is used to find the similarity value between query image and template images are based on the nearest neighbors class. This analytical study was tested using 100 test images. The top three classification results of Arabic (Indian) handwritten recognition use k- nearest neighbors (KNN) are 86% when k = 1, 84% when k = 3, and 83% with k = 5.
机译:手写是指手写(未键入)的结果。人们的写作风格是不一样的。联合国官方语言之一是阿拉伯语,其数字系统称为阿拉伯语(印度)数字。特征的识别可以帮助人们区分图案。可以将分组模式应用于识别图像中对象的机器。连接的组件标签用于分隔字符,以便于识别。 K最近邻用于查找查询图像和模板图像之间的相似度值,这些值基于最近邻类。此分析研究使用100张测试图像进​​行了测试。使用k-最近邻(KNN)的阿拉伯文(印度)手写识别的前三类分类结果在k = 1时为86%,在k = 3时为84%,在k = 5时为83%。

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