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Object classification method utilizing wavelet signatures of a monocular video image

机译:利用单眼视频图像的小波签名的目标分类方法

摘要

A stream of images including an area occupied by at least one object are processed to extract wavelet coefficients, and the extracted coefficients are represented as wavelet signatures that are less susceptible to misclassification due to noise and extraneous object features. Representing the wavelet coefficients as wavelet signatures involves sorting the coefficients by magnitude, setting a coefficient threshold based on the distribution of coefficient magnitudes, truncating coefficients whose magnitude is less than the threshold, and quantizing the remaining coefficients.
机译:处理包括至少一个对象占据的区域的图像流以提取小波系数,并且所提取的系数被表示为小波签名,由于噪声和外来物体特征,该小波签名不太容易被误分类。将小波系数表示为小波签名包括:按幅度对系数进行排序,基于系数幅度的分布设置系数阈值,截断幅度小于阈值的系数以及量化其余系数。

著录项

  • 公开/公告号US2006088219A1

    专利类型

  • 公开/公告日2006-04-27

    原文格式PDF

  • 申请/专利权人 YAN ZHANG;STEPHEN J. KISELEWICH;

    申请/专利号US20040973584

  • 发明设计人 YAN ZHANG;STEPHEN J. KISELEWICH;

    申请日2004-10-26

  • 分类号G06K9/62;E05F15/00;

  • 国家 US

  • 入库时间 2022-08-21 21:46:22

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