Araştırma Makalesi
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DÜŞÜK ÇÖZÜNÜRLÜK VE GRİ GÖRÜNTÜLERDE GERÇEK ZAMANLI CİLT SEGMENTASYONU

Yıl 2021, Cilt: 9 Sayı: Iconat Special Issue 2021, 61 - 64, 24.12.2021
https://doi.org/10.20290/estubtdb.1011578

Öz

Bu çalışmada, literatürde sıklıkla kullanılan cilt bölütleme problemi, anlamsal bölütleme derin öğrenme algoritmaları ile gerçek zamanlı bir web kamerası üzerinde tespit edilecektir. Cilt segmentasyonu, genellikle yüksek çözünürlüklü görüntülerden ayırt edilmesi için yüksek işlem gücü gerektirir. Bu çalışmada kullanılan derin öğrenme algoritması ve önerilen görüntü işleme yöntemi, web kamerası aracılığıyla gerçek zamanlı, çok düşük CPU kullanımı ve gecikmesiz cilt algılama sağlar.

Kaynakça

  • Phung, Son Lam, Abdesselam Bouzerdoum, and Douglas Chai. "Skin segmentation using color pixel classification: analysis and comparison." IEEE transactions on pattern analysis and machine intelligence 27.1 (2005): 148-154.
  • Phung, Son Lam, Douglas Chai, and Abdesselam Bouzerdoum. "Adaptive skin segmentation in color images." 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP'03).. Vol. 3. IEEE, 2003.
  • Phung, Son Lam, Abdesselam Bouzerdoum, and Douglas Chai. "Skin segmentation using color and edge information." Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings.. Vol. 1. IEEE, 2003.
  • Al-Tairi, Zaher Hamid, et al. "Skin segmentation using YUV and RGB color spaces." Journal of information processing systems 10.2 (2014): 283-299.
  • Gasparini, Francesca, and Raimondo Schettini. "Skin segmentation using multiple thresholding." Internet Imaging VII. Vol. 6061. International Society for Optics and Photonics, 2006.
  • Filali, Youssef, et al. "A study of lesion skin segmentation, features selection and classification approaches." 2018 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE, 2018.
  • Lahoti, Sakshi, et al. "Android based american sign language recognition system with skin segmentation and SVM." 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, 2018.
  • Reshna, S., and M. Jayaraju. "Spotting and recognition of hand gesture for Indian sign language recognition system with skin segmentation and SVM." 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE, 2017.
  • [Murugan, A., S. Anu H. Nair, and KP Sanal Kumar. "Detection of skin cancer using SVM, random forest and kNN classifiers." Journal of medical systems 43.8 (2019): 1-9.
  • http://cs-chan.com/downloads_skin_dataset.html

REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES

Yıl 2021, Cilt: 9 Sayı: Iconat Special Issue 2021, 61 - 64, 24.12.2021
https://doi.org/10.20290/estubtdb.1011578

Öz

In this study, the skin segmentation problem, which is frequently used in the literature, will be detected on a real-time webcam with semantic segmentation deep learning algorithms. Skin segmentation generally requires high processing power to distinguish it from images with high resolution. The deep learning algorithm and the proposed image processing method used in this study provide real-time, very low CPU usage, and lag-free skin detection via webcam.

Kaynakça

  • Phung, Son Lam, Abdesselam Bouzerdoum, and Douglas Chai. "Skin segmentation using color pixel classification: analysis and comparison." IEEE transactions on pattern analysis and machine intelligence 27.1 (2005): 148-154.
  • Phung, Son Lam, Douglas Chai, and Abdesselam Bouzerdoum. "Adaptive skin segmentation in color images." 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP'03).. Vol. 3. IEEE, 2003.
  • Phung, Son Lam, Abdesselam Bouzerdoum, and Douglas Chai. "Skin segmentation using color and edge information." Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings.. Vol. 1. IEEE, 2003.
  • Al-Tairi, Zaher Hamid, et al. "Skin segmentation using YUV and RGB color spaces." Journal of information processing systems 10.2 (2014): 283-299.
  • Gasparini, Francesca, and Raimondo Schettini. "Skin segmentation using multiple thresholding." Internet Imaging VII. Vol. 6061. International Society for Optics and Photonics, 2006.
  • Filali, Youssef, et al. "A study of lesion skin segmentation, features selection and classification approaches." 2018 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE, 2018.
  • Lahoti, Sakshi, et al. "Android based american sign language recognition system with skin segmentation and SVM." 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, 2018.
  • Reshna, S., and M. Jayaraju. "Spotting and recognition of hand gesture for Indian sign language recognition system with skin segmentation and SVM." 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE, 2017.
  • [Murugan, A., S. Anu H. Nair, and KP Sanal Kumar. "Detection of skin cancer using SVM, random forest and kNN classifiers." Journal of medical systems 43.8 (2019): 1-9.
  • http://cs-chan.com/downloads_skin_dataset.html
Toplam 10 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Utku Kaya 0000-0003-2378-9748

Abidin Kılıç 0000-0003-4567-5207

Yayımlanma Tarihi 24 Aralık 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 9 Sayı: Iconat Special Issue 2021

Kaynak Göster

APA Kaya, U., & Kılıç, A. (2021). REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES. Eskişehir Teknik Üniversitesi Bilim Ve Teknoloji Dergisi B - Teorik Bilimler, 9(Iconat Special Issue 2021), 61-64. https://doi.org/10.20290/estubtdb.1011578
AMA Kaya U, Kılıç A. REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler. Aralık 2021;9(Iconat Special Issue 2021):61-64. doi:10.20290/estubtdb.1011578
Chicago Kaya, Utku, ve Abidin Kılıç. “REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES”. Eskişehir Teknik Üniversitesi Bilim Ve Teknoloji Dergisi B - Teorik Bilimler 9, sy. Iconat Special Issue 2021 (Aralık 2021): 61-64. https://doi.org/10.20290/estubtdb.1011578.
EndNote Kaya U, Kılıç A (01 Aralık 2021) REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler 9 Iconat Special Issue 2021 61–64.
IEEE U. Kaya ve A. Kılıç, “REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES”, Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler, c. 9, sy. Iconat Special Issue 2021, ss. 61–64, 2021, doi: 10.20290/estubtdb.1011578.
ISNAD Kaya, Utku - Kılıç, Abidin. “REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES”. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler 9/Iconat Special Issue 2021 (Aralık 2021), 61-64. https://doi.org/10.20290/estubtdb.1011578.
JAMA Kaya U, Kılıç A. REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler. 2021;9:61–64.
MLA Kaya, Utku ve Abidin Kılıç. “REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES”. Eskişehir Teknik Üniversitesi Bilim Ve Teknoloji Dergisi B - Teorik Bilimler, c. 9, sy. Iconat Special Issue 2021, 2021, ss. 61-64, doi:10.20290/estubtdb.1011578.
Vancouver Kaya U, Kılıç A. REAL-TIME SKIN SEGMENTATION ON LOW RESOLUTION AND GRAY IMAGES. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler. 2021;9(Iconat Special Issue 2021):61-4.