Abstract
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.
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