面向手绘军标图形的旋转自由识别方法
Rotation free recognition of hand-drawn military marking symbols
- 2014年19卷第3期 页码:456-462
网络出版:2014-03-03,
纸质出版:2014
DOI: 10.11834/jig.20140316
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网络出版:2014-03-03,
纸质出版:2014
移动端阅览
在笔式态势标绘应用中,识别手绘点状军标图形面临着图形类别多、图形类别之间相似度高、绘制方向可变等挑战。针对这些困难提出一个面向手绘军标图形的旋转自由识别方案,以识别图形类别和方向角为目标。 首先通过旋转不变的粗分类缩小候选类别范围,然后估计待识别图形与模板图形间的方向夹角并将二者旋转对齐,最后用细化区分方法识别高相似度的图形类别。采用一种结合图形采样点空间分布和局部方向信息的方向Zernike矩特征描述图形样本,通过匹配方向Zernike矩可实现粗分类和旋转角估计。 实验结果表明本文方法的分类准确率和角度估计精度均明显优于基于传统Zernike矩的识别方法。 该方法可有效应用于对在线手绘军标图形进行旋转自由识别的场合。
In pen-based military situation marking systems
recognizing hand-drawn symbols is confronted with several challenges
such as numerous classes of graphic symbols
high similarity between classes
and orientation variation of many rotatable symbols.A rotation free recognition paradigm is presented considering these difficultiesand
aiming at classifying an instance of a symbol as well as estimating its rotation angle. First
rotation invariant coarse classification is performed to narrow the range of candidate classes.Then the rotation angle between the unknown instance and the template instance is estimated. They can be rotationally aligned by compensating the rotation angle between them.Finally
fining classification methods can be applied to distinguish similar symbols.A novel Zernike moments-based descriptor
called DZM
was used to represent hand-drawn symbol samples.It combines the spatial distribution of sample points and their local direction information.By matching DZM features
both coarse classification and rotation angle estimation could be accomplished. Experimental results show that the proposed method outperforms the traditional Zernike moment method in both classification and rotation angle estimation of hand-drawn military situation marking symbols. This method can be applied effectively in rotation free recognition of online hand-drawn military marking symbols.
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