This paper presents a new feature extraction method called sum and difference histograms of elliptical local ternary pattern (SDH-ELTP) for face image retrieval. This technique first calculates sparse local ternary pattern (LTP) in an elliptical shaped neighborhood and then higher order statistical texture information is extracted via sum and difference histograms (SDH) of elliptical LTP features. In sparse elliptical LTP, a 4 point LTP from horizontal and vertical elliptical neighborhoods and 4 point LTP from simple diagonal neighborhood is considered. The SDH is calculated only in relevant directions. Since the sum and difference histogram provides higher order statistical information, the calculation of SDH of elliptical LTP features further enhances the discriminativeness of proposed descriptor. The SDH-ELTP is finally tested on two popular face image databases and the results are compared with several recent state of the art techniques. The SDH-ELTP is low dimensional and show the best retrieval results as compared to all other face image retrieval techniques.

中文翻译：

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通过椭圆局部三元模式的和直方图和差直方图检索人脸图像

本文提出了一种新的特征提取方法，称为椭圆局部三元模式的和和差直方图（SDH-ELTP），用于人脸图像检索。该技术首先计算椭圆形邻域中的稀疏局部三元图案（LTP），然后通过椭圆LTP特征的求和和直方图（SDH）提取高阶统计纹理信息。在稀疏椭圆LTP中，考虑了水平和垂直椭圆邻域的4点LTP和简单对角邻域的4点LTP。SDH仅在相关方向上计算。由于总和和差异直方图提供了更高阶的统计信息，因此椭圆LTP特征的SDH的计算进一步增强了所提出描述符的判别能力。最终，在两个流行的面部图像数据库上对SDH-ELTP进行了测试，并将结果与​​几种最新的技术水平进行了比较。SDH-ELTP是低维的，与所有其他人脸图像检索技术相比，显示出最佳的检索结果。