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An approach of near infrared image accurate orientation and recognition

机译:一种近红外图像精确定位与识别的方法

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This paper proposes an edge extraction algorithm of near infrared image based on 2-spline wavelet transform. Through Hough transform of edge image, object image''s circle structure can be detected, and object image also has an accurate orientation. So we can extract special figure features of object image. Then near infrared images are classified by statistical template matching. All algorithms which are simple and efficient are compiled in VC++ 6.0. The experimental results show that exact digital image processing method can be applied in the field of differentiating paper currency instead of manual judging. This paper is about a new field of infrared image application and a new direction in differentiating the true and the counterfeit.
机译:提出了一种基于2样条小波变换的近红外图像边缘提取算法。通过边缘图像的霍夫变换,可以检测出目标图像的圆形结构,并且目标图像也具有精确的方向。因此,我们可以提取对象图像的特殊图形特征。然后通过统计模板匹配对近红外图像进行分类。所有简单高效的算法均在VC ++ 6.0中进行了编译。实验结果表明,精确的数字图像处理方法可以应用于鉴别纸币的领域,而无需人工判断。本文是关于红外图像应用的新领域,以及辨别真伪的新方向。

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