Skin Segmentation by Using Complex Valued Neural Network with HSV Color Spaces
Öz
Nowadays, digital image processing is useful
tool in daily life for security, surveillance and artificial intelligence
applications. Mainly in nudity alerts and face detection, skin segmentation is
widely preferred method due to its simple background. The main problem in skin
segmentation is skin color variation that result of different percentage of
pigments, number and size of melanin particles in human-being. In literature,
there are rule-based and hybrid models for skin segmentation, however
rule-based algorithm are not enough to overcome skin variety. As hybrid mode
Complex valued neural network (CVNN) and color space transformation is applied to
Skin Segmentation Database from UCI Learning Repository that is collection of
different age and race group human’s skin samples in RGB format.
Anahtar Kelimeler
Kaynakça
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- [4] Bhatt, Rajen B., et al. "Efficient skin region segmentation using low complexity fuzzy decision tree model." India Conference (INDICON), 2009 Annual IEEE. IEEE, 2009.
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- [6] 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.
- [7] Costin, Gertrude-E., and Vincent J. Hearing. "Human skin pigmentation: melanocytes modulate skin color in response to stress." The FASEB journal 21.4 (2007): 976-994.
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Ayrıntılar
Birincil Dil
İngilizce
Konular
-
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
4 Mart 2019
Gönderilme Tarihi
16 Ocak 2019
Kabul Tarihi
4 Mart 2019
Yayımlandığı Sayı
Yıl 2019 Cilt: 3 Sayı: 1