Texture features extraction based on GLCM for face retrieval system

Sundos Abdulameer Alazawi, Narjis Mezaal Shati, Amel H. Abbas

Abstract


Texture features play an important role in most image retrieval techniques to obtain results of high accuracy. In this work, the face image retrieval method considering texture analysis and statistical features has been proposed. Textile features can also be extracted using the GLCM tool. In this research, the GLCM calculation method involves two phases, first: some of the previous image processing techniques work together to get the best results to determine the big object of the face image (center of face image) then, the gray level co-occurrence matrix GLCM is computed for gray face image and then some statistical texture features with second-order are extracted. In the second phase, the facial texture features are retrieved by finding the minimum distance between texture features of an unknown face image with the texture features of face images that are stored in the database system. The experimental results show that the proposed method is capable to achieve high accuracy degree in face image retrieval.

Keywords


Face retrieval; Texture Feature; GLCM; Pattern Recognition

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DOI: http://dx.doi.org/10.21533/pen.v7i3.787

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Copyright (c) 2019 Sundos Abdulameer Alazawi, Narjis Mezaal Shati, Amel H. Abbas

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License