Hand Written Digit Recognition using Machine Learning

R. Sethi, I. Kaushik
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引用次数: 10

Abstract

Hand-written character and digit recognition have been one of the most exigent and engrossing field of pattern recognition and image processing. The main aim of this paper is to demonstrate and represent the work which is related to hand-written digit recognition. The hand-written digit recognition is a very exigent task. In this recognition task, the numbers are not accurately written or scripted as they differ in shape or size; due to which the feature extraction and segmentation of hand-written numerical script is arduous. The vertical and horizontal projections methods are used for the purpose of segmentation in the proposed work. SVM is applied for recognition and classification, while Convex hull algorithm is applied for feature extraction.
使用机器学习的手写数字识别
手写字符和数字识别一直是模式识别和图像处理中最迫切和最引人关注的领域之一。本文的主要目的是展示和展示与手写数字识别相关的工作。手写数字识别是一项非常紧迫的任务。在这个识别任务中,由于数字的形状和大小不同,它们的书写或脚本并不准确;因此,手写体数字文字的特征提取和分割是一项艰巨的任务。在提出的工作中,垂直和水平投影方法用于分割目的。采用支持向量机进行识别分类,凸包算法进行特征提取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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