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首页> 外文期刊>Multimedia Tools and Applications >Human eye location algorithm based on multi-scale self-quotient image and morphological filtering for multimedia big data
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Human eye location algorithm based on multi-scale self-quotient image and morphological filtering for multimedia big data

机译：基于多尺度自商图像和形态学滤波的多媒体大数据人眼定位算法

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摘要

In order to reduce the effect on the eyes location caused by the variation of illumination and expression, this paper proposes a human eye location algorithm based on the multi-scale self-quotient image and morphological filtering. Firstly, the multi-scale self-quotient image is used to offset the lighting effects on the face, then the morphological open-close operation will be taken to enhance the local features around the eyes and relevant coefficient is used to roughly position the eyes. At last, the variance projection method will be used to analyze the roughly-positioned areas and binarize them to position accurately the central point of the eye. The experiments on the images from JAFFE Database, Yale B Database and AR database have shown that the proposed algorithm can well position the center of the eye, and it is robust to deal with the changes of illumination and expressions.
机译：为了减少光照和表情变化对眼睛定位的影响，提出一种基于多尺度自商图像和形态学滤波的人眼定位算法。首先，使用多尺度自商图像来抵消面部的照明效果，然后将进行形态学开闭操作以增强眼睛周围的局部特征，并使用相关系数来粗略定位眼睛。最后，将使用方差投影法分析粗略定位的区域并将其二值化以准确定位眼睛的中心点。在JAFFE数据库，Yale B数据库和AR数据库的图像上进行的实验表明，该算法能够很好地定位眼睛的中心，并且能够很好地应对光照和表情的变化。

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