Hayvan Derisinin Kusur Tespitinde Makine Öğrenmesi Tekniklerinin Kullanımı – Literatür Taraması

Year 2024, Volume: 6 Issue: 2, 58 - 67, 15.12.2024

Hasan Onur Ataç , Ahmet Kayabaşı , Muhammet Fatih Aslan

https://doi.org/10.55213/kmujens.1487273

Abstract

Derinin insan hayatında ilk çağlardan beri var olduğu tahmin edilmektedir. Nitekim ilk başlarda sadece soğuktan ve rüzgârdan korunmak için kullanıldığı düşünülürken günümüzde deri, dayanıklılığı ve estetikliği sebebiyle moda, mobilya ve otomotiv gibi devasa sektörlerde çok geniş bir kullanım alanına sahiptir. Küresel deri pazarı her geçen yıl daha da büyümektedir. Bu durum deri üretiminde akıllı yaklaşımların önemini her geçen gün artırmaktadır. Tabakhanelerde deri ürünlerindeki yüzey kusurlarını tespit edebilmek için tecrübeli insan denetçilerin kullanılması uzun zamandır süregelen bir uygulamadır. Ancak bu yöntem, yorucu, zaman alıcı, hatalara açık ve kişinin tecrübesine göre değişkendir. Kaliteli deri ürünlerinde hata payının düşük olması ekonomik olarak ciddi öneme sahiptir. Sektördeki insan hatalarından kurtulmak ve verilen kararları nesnelleştirebilmek adına deri yüzeyindeki kusurların otomatik tespit edilebilmesi ihtiyacı ortaya çıkmıştır. Bu çalışmada hayvan derisinin kusurlarını tespit edebilmek amacı ile makine öğrenmesi tekniklerini kullanan çalışmalar hakkında literatür taraması yapılmıştır. Görüntü analizi ve makine öğrenmesi yöntemleri ile deri yüzeylerindeki kusurları tespit etme yöntemlerinin detaylı bir incelemesi yapılmıştır. Bu alanda gelecekte yapılacak çalışmaları teşvik etmek amacı ile zorluklar ve gelişim evreleri sunulmuştur.

Keywords

Hayvan derisi, yüzey kusur tespiti, bilgisayar görüsü, makine öğrenmesi

Use of Machine Learning Techniques in Defect Detection of Leather - Review

Abstract

It is estimated that leather has existed in human life since ancient times. As a matter of fact, while it was initially thought that it was used only to protect from cold and wind, today leather has a wide range of usage in huge sectors such as fashion, furniture and automotive, due to its durability and aesthetics. The global leather market is growing every year. This situation increases the importance of smart approaches in leather production day by day. It has been a long-standing practice for tanneries to use experienced human inspectors to detect surface defects in leather products. However, this method is tiring, time-consuming, prone to errors and varies depending on the person's experience. A low margin of error in determining the quality of leather products is of serious economic importance. In order to get rid of human errors in the sector and to objectify the decisions made, the need to automatically detect flaws on the leather surface has emerged. In this study, a literature review was conducted on studies using machine learning techniques to detect defects in animal leather. A detailed review of methods for detecting defects on leather surfaces using image analysis and machine learning methods was conducted. Challenges and stages of development are presented with the aim of encouraging future work in this field.

Keywords

Leather, surface defect detection, computer vision, machine learning

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