Mask Fitting on Face Images Based on Morphing and Masked Face Recognition

Yıl 2023, , 12 - 21, 25.04.2023

Asuman Günay Yılmaz , Eyup Gedikli , Omar Alhori

https://doi.org/10.19113/sdufenbed.1059761

Öz

Viruses such as Covid-19 cause serious respiratory diseases, making the use of face masks important. For this reason, it is expected that face recognition and verification systems can also work with masked faces. There are no masked faces in the data sets created for face recognition systems, and today, masks of different models and patterns can be used in daily life. These reduce the success of face recognition systems. In this study, first, a wide masked face data set was produced by fitting different types of masks to the images in the existing face datasets. In the production of masked faces close to nature, the automatic mask fitting process was carried out with the image morphing technique. Then, a deep learning based model was developed for the recognition of masked/unmasked faces, and the dataset created with the automatic mask fitting technique was used to train the model. In the experiments using CASIA-WebFace and LFW (Labeled Faces in the Wild) datasets, masked face recognition performance was achieved over 96.5%.

Anahtar Kelimeler

Masked face recognition, Biometric identification, Automatic mask fitting, Image morphing, Deep learning

Yüz Görüntülerine Morflemeye Dayalı Maske Giydirme ve Maskeli Yüz Tanıma

Öz

Covid-19 gibi virüslerin ciddi solunum yolu hastalıklarına neden olması, yüz maskelerinin kullanımını önemli hale getirmiştir. Bu nedenle yüzden kişi doğrulama ve tanıma yapan sistemlerin maskeli yüzler üzerinde de çalışabilmesi beklenmektedir. Yüz tanıma sistemleri için oluşturulan veri setlerinde maskeli yüzler olmamakla birlikte günümüzde farklı model ve desenlerde maskeler kullanılabilmektedir. Bunlar yüz tanıma sistemlerinin başarısını düşürmektedir. Bu çalışmada öncelikle maskeli yüz veri seti üretmek için mevcut yüz veri setlerine farklı tipteki maskelerin giydirilmesine çalışılmıştır. Morfleme tekniği kullanılarak yüzün pozisyonlarına uygun olarak doğala yakın otomatik giydirme işlemi gerçekleştirilmiştir. Daha sonra maskeli/maskesiz yüzlerin tanınması için derin
öğrenmeye dayalı bir model geliştirilmiş ve otomatik maske giydirme tekniği ile oluşturulan veri seti denenmiştir. CASIA-WebFace ve LFW (Labeled Faces in the Wild) veri setleri kullanılarak gerçekleştirilen deneylerde %96.5’in üzerinde maskeli yüz tanıma başarımı elde edilmiştir.

Anahtar Kelimeler

Maskeli yüz tanıma, Biyometrik kimlik tanıma, Otomatik maske giydirme, Görüntü morfleme, Derin öğrenme

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