Gender Classification from Face Images by Using Local Binary Pattern and Gray-Level Co-Occurrence Matrix
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPIE-INT SOC OPTICAL ENGINEERING
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Gender is an important step for human computer interactive processes and identification. Human face image is one of the important sources to determine gender. In the present study, gender classification is performed automatically from facial images. In order to classify gender, we propose a combination of features that have been extracted face, eye and lip regions by using a hybrid method of Local Binary Pattern and Gray-Level Co-Occurrence Matrix. The features have been extracted from automatically obtained face, eye and lip regions. All of the extracted features have been combined and given as input parameters to classification methods (Support Vector Machine, Artificial Neural Networks, Naive Bayes and k-Nearest Neighbor methods) for gender classification. The Nottingham Scan face database that consists of the frontal face images of 100 people (50 male and 50 female) is used for this purpose. As the result of the experimental studies, the highest success rate has been achieved as 98% by using Support Vector Machine. The experimental results illustrate the efficacy of our proposed method.
Açıklama
10th International Conference on Machine Vision (ICMV) -- NOV 13-15, 2017 -- Vienna, AUSTRIA
Anahtar Kelimeler
Gender classification, gray-level co-occurrence matrix, local binary pattern, image processing
Kaynak
TENTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2017)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
10696
