Extraction of Cattle Retinal Vascular Patterns with Different Segmentation Methods
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 a...
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| Format: | Article |
| Language: | English |
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Sakarya University
2024-12-01
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| Series: | Sakarya University Journal of Computer and Information Sciences |
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| Online Access: | https://dergipark.org.tr/en/download/article-file/4039542 |
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| author | Ahmet Saygılı Nihat Eren Özmen Özgür Aksoy Alican Yılmaz Uğur Aydın Celal Şahin Ermutlu Muhammed Akyüzlü Pınar Cihan |
| author_facet | Ahmet Saygılı Nihat Eren Özmen Özgür Aksoy Alican Yılmaz Uğur Aydın Celal Şahin Ermutlu Muhammed Akyüzlü Pınar Cihan |
| author_sort | Ahmet Saygılı |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-3235454b419f4c9aa0be8bebb9e0fbc2 |
| institution | Kabale University |
| issn | 2636-8129 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Sakarya University |
| record_format | Article |
| series | Sakarya University Journal of Computer and Information Sciences |
| spelling | doaj-art-3235454b419f4c9aa0be8bebb9e0fbc22025-01-07T09:08:00ZengSakarya UniversitySakarya University Journal of Computer and Information Sciences2636-81292024-12-017337838810.35377/saucis...150915028Extraction of Cattle Retinal Vascular Patterns with Different Segmentation MethodsAhmet Saygılı0https://orcid.org/0000-0001-8625-4842Nihat Eren Özmen1https://orcid.org/0000-0002-0053-3865Özgür Aksoy2https://orcid.org/0000-0002-4800-6079Alican Yılmaz3https://orcid.org/0000-0001-7042-1749Uğur Aydın4https://orcid.org/0000-0001-5756-4841Celal Şahin Ermutlu5https://orcid.org/0000-0002-8923-7682Muhammed Akyüzlü6https://orcid.org/0009-0006-3940-520XPınar Cihan7https://orcid.org/0000-0001-7958-7251TEKİRDAĞ NAMIK KEMAL ÜNİVERSİTESİTEKİRDAĞ NAMIK KEMAL ÜNİVERSİTESİKAFKAS ÜNİVERSİTESİKAFKAS ÜNİVERSİTESİKAFKAS ÜNİVERSİTESİKAFKAS ÜNİVERSİTESİTEKİRDAĞ NAMIK KEMAL ÜNİVERSİTESİTEKİRDAĞ NAMIK KEMAL ÜNİVERSİTESİIn 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.https://dergipark.org.tr/en/download/article-file/4039542animal retina segmentationclahefuzzy c-meansk-meanslevel-set |
| spellingShingle | Ahmet Saygılı Nihat Eren Özmen Özgür Aksoy Alican Yılmaz Uğur Aydın Celal Şahin Ermutlu Muhammed Akyüzlü Pınar Cihan Extraction of Cattle Retinal Vascular Patterns with Different Segmentation Methods Sakarya University Journal of Computer and Information Sciences animal retina segmentation clahe fuzzy c-means k-means level-set |
| title | Extraction of Cattle Retinal Vascular Patterns with Different Segmentation Methods |
| title_full | Extraction of Cattle Retinal Vascular Patterns with Different Segmentation Methods |
| title_fullStr | Extraction of Cattle Retinal Vascular Patterns with Different Segmentation Methods |
| title_full_unstemmed | Extraction of Cattle Retinal Vascular Patterns with Different Segmentation Methods |
| title_short | Extraction of Cattle Retinal Vascular Patterns with Different Segmentation Methods |
| title_sort | extraction of cattle retinal vascular patterns with different segmentation methods |
| topic | animal retina segmentation clahe fuzzy c-means k-means level-set |
| url | https://dergipark.org.tr/en/download/article-file/4039542 |
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