HU MOMENTLERI İLE GÖRÜNTÜ İŞLEME TABANLI GÖMLEK BOYUT TESPITI

Ethem Sefa Küçükyilmaz; Erhan Akın

doi:10.17780/ksujes.1681084

EN TR

HU MOMENTLERI İLE GÖRÜNTÜ İŞLEME TABANLI GÖMLEK BOYUT TESPITI

Abstract

This study proposes a hybrid classification model for the automatic detection of shirt sizes in textile quality control processes. The model integrates Hu moment-based numerical features with a convolutional neural network (CNN) architecture, combining the interpretability of traditional image processing with the classification performance of deep learning methods. The proposed CNN+Hu moments approach was trained and tested on a controlled dataset comprising various shirt size categories (XXS, XS, S, M, L, XL). Experimental results demonstrate that the hybrid model significantly outperforms classical machine learning algorithms such as Support Vector Machines (SVM) and KDTree in terms of accuracy and robustness. With its low cost, explainability, and effectiveness, this approach offers a new dimension to quality control systems in the textile industry.

Keywords

HU MOMENTLERI İLE GÖRÜNTÜ İŞLEME TABANLI GÖMLEK BOYUT TESPITI

Öz

Bu çalışma, tekstil sektöründeki kalite kontrol süreçlerinde, gömlek boyutlarının otomatik olarak tespiti için hibrit bir sınıflandırma modeli önermektedir. Model, Hu moment tabanlı sayısal özelliklerin evrişimsel sinir ağı (CNN) yapısıyla bütünleştirilmesiyle oluşturulmuştur. Bu sayede hem geleneksel görüntü işleme temelli açıklanabilirlik sağlanmış hem de derin öğrenme yöntemlerinin sınıflandırma başarımı elde edilmiştir. Geliştirilen model, kontrollü bir veri kümesinde uygulanarak farklı beden grupları (XXS, XS, S, M, L, XL) üzerinde test edilmiştir. Elde edilen sonuçlar, önerilen CNN+Hu moment hibrit yaklaşımının, klasik makine öğrenmesi algoritmalarına (SVM, KDTree) kıyasla daha yüksek doğruluk ve kararlılık sunduğunu göstermektedir. Bu yönüyle çalışma, kalite kontrol süreçlerine yeni bir boyut kazandırmakta ve tekstil sektörüne yönelik düşük maliyetli, açıklanabilir ve etkin bir çözüm sunmaktadır.

Anahtar Kelimeler

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Görüntü İşleme

Bölüm

Araştırma Makalesi

Yazarlar

Ethem Sefa Küçükyilmaz ^*
0009-0008-6912-1851
Türkiye

Erhan Akın
0000-0001-6476-9255
Türkiye

Yayımlanma Tarihi

3 Eylül 2025

Gönderilme Tarihi

22 Nisan 2025

Kabul Tarihi

16 Temmuz 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 28 Sayı: 3

DOI

https://doi.org/10.17780/ksujes.1681084

IZ

https://izlik.org/JA94UH52NF

Kaynak Göster

RIS / Bibtex

APA

Küçükyilmaz, E. S., & Akın, E. (2025). HU MOMENTLERI İLE GÖRÜNTÜ İŞLEME TABANLI GÖMLEK BOYUT TESPITI. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(3), 1407-1417. https://doi.org/10.17780/ksujes.1681084