Farklı Klinik Işıklarında Metamerizmi Önlemek İçin Renk Anları Kullanılarak Makine Öğrenmesi Tabanlı Diş Rengi Değerlendirmesi

Öz

Protetik diş tedavisinde doğru renk seçimi, hem doğal bir estetik görünüm elde edilmesi hem de hastanın tedaviye olan memnuniyetinin artırılması açısından büyük önem taşımaktadır. Ancak, bu süreç pek çok teknik ve çevresel faktörden etkilenmektedir. Özellikle klinik ve laboratuvar ortamlarındaki değişen ışık kaynakları, renk algısında yanıltıcı sonuçlara yol açan metamerizm sorununa neden olmaktadır. Bu çalışma, farklı ışık kaynaklarında renk tespiti yaparak metamerizmin etkisini azaltan, geleneksel renk eşleştirme yöntemlerinin subjektifliğini ortadan kaldıran ve maliyetli ölçüm cihazlarına alternatif sunan bir yöntem önermektedir. Vita 3D Master renk skalasında bulunan 29 renk örneği, dört farklı klinik ışık kaynağında beşer kez görüntülenmiştir. RGB, LAB ve HSV renk uzaylarında renk anları kullanılarak öznitelik çıkarımı yapılmıştır. Bu verilerle oluşturulan veri setleri üzerinde farklı makine öğrenmesi algoritmaları ile deneysel çalışmalar gerçekleştirilmiştir. Sonuçta, dört klinik ışık koşulunun sınıflandırılmasında %100, 29 Vita renginin ışıktan bağımsız sınıflandırılmasında %85, beyaz ışık altında %100, doğal ışık altında %97, flaş ışığında %92 ve sarı ışık altında %94 doğruluk oranları elde edilmiştir. Bu bulgular, geleneksel veya maliyetli renk seçim süreçlerinin sınırlamalarının aşılabileceğini ve metamerizmin makine öğrenmesi teknikleriyle azaltılabileceğini göstermiştir.

Anahtar Kelimeler

• Renk anları
• Makine öğrenmesi
• Vita renk uyumu
• Metamerizm
• Protez diş tedavisi

Machine Learning-Based Tooth Color Assessment Using Color Moments to Prevent Metamerism in Different Clinical Lights

Öz

Choosing the right shade in prosthodontic treatment is of great importance in terms of achieving a natural aesthetic appearance and increasing the patient's satisfaction with the treatment. However, this process is affected by many technical and environmental factors. In particular, variable light sources in clinical and laboratory environments cause the problem of metamerism, which leads to misleading results in color perception. This study proposes a method that reduces the effect of metamerism by detecting color under different light conditions, eliminates the subjectivity of traditional color matching methods and offers an alternative to costly measurement devices. The 29 color samples from the Vita 3D Master shade guide were imaged five times each in four different clinical light conditions. Feature extraction was performed using color moments in RGB, LAB and HSV color spaces. Experimental studies were carried out with different machine learning algorithms on the datasets created with these data. As a result, 100% accuracy was obtained for the classification of four clinical light conditions, 85% for the light-independent classification of 29 Vita colors, 100% under white light, 97% under natural light, 92% under flash light and 94% under yellow light. These findings demonstrated that the limitations of traditional or costly color selection processes can be overcome and metamerism can be reduced by machine learning techniques.

Anahtar Kelimeler

• Color Moments
• Machine Learning
• Vita Shade Matching
• Metamerism
• Prosthetic Tooth
• Treatment

Kaynakça

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