| Yazarlar (8) |
Pınar Cihan
Tekirdağ Namık Kemal Üniversitesi, Türkiye |
|
Ahmet Saygılı
Tekirdağ Namık Kemal Üniversitesi, Türkiye |
|
Muhammed Akyüzlü
|
|
Nihat Eren Özmen
Türkiye |
Prof. Dr. Celal Şahin ERMUTLU
Türkiye |
Doç. Dr. Uğur AYDIN
Türkiye |
Arş. Gör. Alican YILMAZ
Türkiye |
Prof. Dr. Özgür AKSOY
Türkiye |
| Özet |
| In the field of animal husbandry, the process of animal identification and recognition is challenging, time-consuming, and costly. In Türkiye, the ear tagging method is widely used for animal identification. However, this traditional method has many significant disadvantages such as lost tags, the ability to copy and replicate tags, and negative impacts on animal welfare. Therefore, in some countries, biometric identification methods are being developed and used as alternatives to overcome the disadvantages of traditional methods. Retina vessel patterns are a biometric identifier with potential in biometric identification studies. Preprocessing steps and vessel segmentation emerge as crucial steps in image processing-based identification and recognition systems. In this study, conducted in the Kars region of Türkiye, a series of preprocessing steps were applied to retinal images collected from cattle. Fuzzy c-means, k-means, and level-set methods were utilized for vessel segmentation. The segmented vascular structures obtained with these methods were comparatively analyzed. As a result of the comparison, it was observed that all models successfully performed retinal main vessel structure segmentation, fine vessels were successfully identified with fuzzy c-means, and spots in retinal images were detected only by the level-set method. Evaluating the success of these methods in identification, recognition, or disease detection will facilitate the development of successful systems. |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayımlanan tam makale |
| Dergi Adı | SAKARYA UNIVERSITY JOURNAL OF COMPUTER AND INFORMATION SCIENCES |
| Dergi ISSN | 2636-8129 |
| Dergi Tarandığı Indeksler | TR DİZİN |
| Makale Dili | İngilizce |
| Basım Tarihi | 11-2024 |
| Cilt No | 7 |
| Sayı | 3 |
| Sayfalar | 378 / 388 |
| Doi Numarası | 10.35377/saucis…1509150 |
| Makale Linki | chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/http://saucis.sakarya.edu.tr/en/download/article-file/4039542 |
| Atıf Sayıları |
