Polimerik kaplamalı kumaşlarda görüntü işleme ile niceleme ve karakterizasyon uygulaması

Bu çalışmada gri seviye eş oluşum matrisi ile fraktal boyut kullanılarak pamuk kumaş üzerine uygulanan polimerik kaplama içerisindeki taneciklerin dağılımı incelenmiştir. Kumaş yüzeyine farklı miktarlarda nano boyutta tanecik içeren kaplama formülasyonları uygulanmış daha sonra kumaşın termal gravimetrik yöntem (thermo gravimetric analysis-TGA) ile yanmazlık özellikleri incelenmiştir. Kaplanan kumaş yüzeyleri üzerinden optik mikroskop ile görüntüler elde edilmiş ve bu görüntüler gri seviye ve fraktal boyut özellik çıkarımında kullanılmıştır.  Farklı miktarlarda nano tanecik içeren kaplı kumaşların mikroskop görüntüleri, görüntü işleme tekniği ile analiz edilerek nicelendirme ve sınıflandırma işlemleri yapılmıştır. Görüntü işleme ile elde edilen sonuçlar TGA ile bulunan deneysel bulgularla mukayese edilmiştir. Görüntü işleme tekniği ile özellik çıkarılarak en iyi kaplama kalitesine sahip numunenin, %5 montmorillonit (MMT) içeren örnek olduğu tespit edilmiştir. Numuneler arasındaki ortalama sınıflandırma başarısı %92,5 olarak elde edilmiştir.

Application of image processing for quantization and characterization of fabrics with polymeric coatings

In this study, the dispersion quality of particles on polymeric coating formulations from cotton fabric surfaces was investigated by using gray level co-occurrence matrix and fractal dimension. Coating formulations with various nano particle inclusions were applied on cotton fabrics. The flame retardant property of coated fabrics were examined by thermal gravimetric analysis (TGA). Images from the coated fabric surfaces were obtained by using optical microscopy and then these images were used in gray level and fractal dimension feature extraction processes. The microscopic images of the coated fabrics in various particle amounts were analyzed by using the image processing technique, and then classification and quantization processes were performed. The results of the image processing were compared to the results of TGA. The sample containing 5% montmorillonite (MMT) was found as having the best coating quality level by using feature extraction method in image processing. The average classification performance among all the samples was found as 92.5%.

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