Static Sign Language Recognition Based on Edge Gradient Direction Histogram

SUN Li-juan; ZHANG Li-cai

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Static Sign Language Recognition Based on Edge Gradient Direction Histogram

更新时间：2026-09-04

- Static Sign Language Recognition Based on Edge Gradient Direction Histogram
- Vol. 27, Issue 3, Pages: 148-150(2010)
- 作者机构：
  
  西安建筑科技大学机构信息与控制工程学院,陕西,西安,710055
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2010
- 稿件说明：
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孙丽娟, 张立材. 基于边缘梯度方向直方图的静态手语识别[J]. 微电子学与计算机, 2010, 27(3): 148-150,153.

SUN Li-juan, ZHANG Li-cai. Static Sign Language Recognition Based on Edge Gradient Direction Histogram[J]. 2010, 27(3): 148-150.
孙丽娟, 张立材. 基于边缘梯度方向直方图的静态手语识别[J]. 微电子学与计算机, 2010, 27(3): 148-150,153. DOI：

SUN Li-juan, ZHANG Li-cai. Static Sign Language Recognition Based on Edge Gradient Direction Histogram[J]. 2010, 27(3): 148-150. DOI：

摘要

文中采用边缘梯度方向直方图作为手势的特征矢量进行手语识别

建立归一化的边缘梯度直方图

使用欧氏距离模板匹配法进行手势的特征匹配

手势特征矢量之间的识别速度较快.实验表明:该方法对图像亮度、缩放、平移具有不变性

该方法计算简单、快速

可以用于手语识别系统.

Abstract

In this paper

we use the edge gradient direction histogram as a feature vector for sign language recognition

set up normalized edge gradient direction histogram.The compare of gesture feature vector is rapid used Euclidean distance template matching method.The experiments result shows that the algorithm has the robustness to scene illumination changes

position translation and scale.This method is simple and fast

so we can apply this method to the hand gesture recognition system.

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