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DOI

http://dx.doi.org/10.25098/4.1.28
Issue 
Vol 4- Issue 1

JUNE 2020

Hybrid Discrete Wavelet Transform and Local Binary Pattern for Ethnicity Identification from Facial Images algorithm

Hawkar Omar Ahmed

Department of Information Technology, College of Commerce, University of Sulaimani, Sulaimani, Iraq

Department of Information Technology, University College of Goizha, Sulaimani, Iraq

[email protected]

Received : 6-3-2020                                       Revised: 2-5-2020

Accepted :  10-5-2020                                    Published :30-6-2020

Abstract:

Human facial images provide significant amount of demographic information such as ethnicity, age, and gender. Ethnicity identification involves automatic estimation of ethnicity which has many potential applications ranging from forensics to social media. This paper concerns the ethnicity identification from facial images by extracting Local Binary Pattern (LBP) in Discrete Wavelet Transform (DWT) domain. Furthermore, K-Nearest Neighbor (K-NN) classification technique is used to classify the selected feature vector. We shall demonstrate that the proposed approach has significant impact on improving accuracy compared to existing approaches. The performance of the proposed approach has been evaluated via experiments conducted on our collected dataset of 950 facial images. Experimental results illustrate that the proposed approach reaches an accuracy rate of 90.27% of ethnicity identification.

Keywords

Discrete Wavelet Transform (DWT), Local Binary Pattern (LBP), City Block, K-Nearest Neighbor (KNN)

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