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Image-HOG-Feature

于 2023-08-06 发布 文件大小:1.52 kB
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HOG特征计算的步骤:(1)将输入的彩图转换为灰度图;(2)采用Gamma校正法对输入图像进行颜色空间的标准化(归一化);目的是调节图像的对比度,降低图像局部的阴影和光照变化所造成的影响,同时可以抑制噪音的干扰;(3)计算梯度;主要是为了捕获轮廓信息,同时进一步弱化光照的干扰。(4)将梯度投影到单元的梯度方向;目的是为局部图像区域提供一个编码,(5)将所有单元格在块上进行归一化;归一化能够更进一步对光照、阴影和边缘进行压缩,通常,每个单元格由多个不同的块共享,但它的归一化是基于不同块的,所以计算结果也不一样。因此,一个单元格的特征会以不同的结果多次出现在最后的向量中。我们将归一化之后的块描述符就称之为HOG描述符。(6)收集得到检测空间所有块的HOG特征;该步骤就是将检测窗口中所有重叠的块进行HOG特征的收集,并将它们结合成最终的特征向量供分类使用。

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