{
    "article_id": 296,
    "public_id": "7dafa95e-8f3c-4e99-a38f-f041ce882e12",
    "internal_identifier": null,
    "source_identifier": "1:21",
    "status": "published",
    "type": "research_article",
    "title": "Gürültünün Tohumlu Alan Genişletme Tabanlı Bölütleme Sonucuna Etkisinin Nicemsel Olarak Belirlenmesi",
    "title_secondary": null,
    "abstract": "Görüntü bölütleme, görüntü işlemenin önemli aşamalarından biridir ve SRG (Seeded Region Growing – Tohumlu Bölge Genişletme) en bilinen bölge tabanlı bölütleme tekniklerindendir. Bu çalışmada tohum seçimlerinin, tohumlu alan genişletmedeki başarıya etkisi incelenmiş ve farklı gürültü yoğunluklarında tohumlu alan genişletmenin başarısı karşılaştırılmıştır. Yapılan testlerde Weizmann tek nesneli görüntü veritabanı kullanılmıştır. Daha sonra kullanıcı yardımıyla 3 farklı tohum alanı seçilmiştir. Tohumlardan ikisinin seçiminde nesne ve arka plan için birer tohum alanı işaretlenmiş, diğer seçimde ise hem nesne hem de arka plan için birden fazla tohum alanı işaretlenmiştir. Ayrıca ilgili görüntülere farklı tip ve yoğunlukta gürültü eklenmiştir. Sonuç olarak tüm bu görüntüler, işaretlenmiş tohum alanları kullanılarak bölütlenmiş ve bölütleme başarısı F-score olarak elde edilmiştir.  ",
    "language": "tr",
    "english_title": "Quantitative Determination of the Effect of Noise on Seed Region Growing-Based Segmentation Results",
    "english_abstract": "Image segmentation is a crucial stage in image processing, and SRG (Seeded Region Growing) is one of the best-known region-based segmentation techniques. This study investigates the effect of seed selection on the success of seeded region growing and compares the success of seeded region growing at different noise densities. A Weizmann single-object image database was used in the tests. Three different seed regions were then selected with user assistance. In two of the seed selections, one seed region was marked for the object and one for the background, while in the other selection, multiple seed regions were marked for both the object and the background. Additionally, different types and densities of noise were added to the relevant images. Finally, all these images were segmented using the marked seed regions, and the segmentation success was obtained as an F-score.",
    "doi": null,
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    "resource_url": "https://www.set-science.com/a/7dafa95e-8f3c-4e99-a38f-f041ce882e12",
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            "given": "Mürsel Ozan",
            "family": "İncetaş",
            "full": "Mürsel Ozan İncetaş",
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            "email": "ozan.incetas@beun.edu.tr",
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                {
                    "name": "Bülent Ecevit University",
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            ]
        },
        {
            "public_id": "8f3ff31a-ffdc-4868-84b9-af2fd968910e",
            "given": "Mahmut",
            "family": "Kılıçaslan",
            "full": "Mahmut Kılıçaslan",
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            "email": "m.kilicaslan@ankara.edu.tr",
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            "affiliations": [
                {
                    "name": "Ankara University",
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            ]
        },
        {
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            "given": "Ufuk",
            "family": "Tanyeri",
            "full": "Ufuk Tanyeri",
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            "email": "ufuktanyeri@ankara.edu.tr",
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            "sequence": "additional",
            "affiliations": [
                {
                    "name": "Ankara University",
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        },
        {
            "public_id": "a116a7d1-2dc1-44d9-adb1-0fbf7909de7c",
            "given": "Burcu",
            "family": "Yakışır Girgin",
            "full": "Burcu Yakışır Girgin",
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            "email": "bygirgin@ankara.edu.tr",
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                {
                    "name": "Ankara University",
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        },
        {
            "public_id": "d5c223f1-51b2-4cc6-8978-08acc190d2cd",
            "given": "Zübeyr",
            "family": "Aydemir",
            "full": "Zübeyr Aydemir",
            "literal": null,
            "orcid": null,
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            "email": "zubeyraydemir@beun.edu.tr",
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                {
                    "name": "Bülent Ecevit University",
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    ],
    "keywords": [],
    "translations": [
        {
            "language": "en",
            "title": "Quantitative Determination of the Effect of Noise on Seed Region Growing-Based Segmentation Results",
            "abstract": "Image segmentation is a crucial stage in image processing, and SRG (Seeded Region Growing) is one of the best-known region-based segmentation techniques. This study investigates the effect of seed selection on the success of seeded region growing and compares the success of seeded region growing at different noise densities. A Weizmann single-object image database was used in the tests. Three different seed regions were then selected with user assistance. In two of the seed selections, one seed region was marked for the object and one for the background, while in the other selection, multiple seed regions were marked for both the object and the background. Additionally, different types and densities of noise were added to the relevant images. Finally, all these images were segmented using the marked seed regions, and the segmentation success was obtained as an F-score.",
            "keywords": [
                "tohumlu alan genişletme; gürültü; bölütleme; tohum seçimi"
            ]
        }
    ],
    "subjects": [],
    "subject_names": [],
    "published_date": "2017-12-08",
    "published_year": "2017",
    "received_date": null,
    "accepted_date": null,
    "volume": "1",
    "issue": null,
    "page_first": "98",
    "page_last": "101",
    "article_number": null,
    "conference": {
        "short_name": "ISMSIT2017",
        "full_title": "International Symposium on Multidisciplinary Studies and Innovative Technologies",
        "name": "International Symposium on Multidisciplinary Studies and Innovative Technologies",
        "acronym": "ISMSIT2017",
        "location": "Tokat, Türkiye",
        "start_date": "2017-12-02",
        "end_date": null,
        "public_id": "a63b4822-97d6-4580-83b6-aec40f3f7964"
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    "proceedings": {
        "title": "International Symposium on Multidisciplinary Studies and Innovative Technologies",
        "series_title": "Setsci conference indexing system",
        "publisher": "SET Technology",
        "isbn": "978-605-81988-1-4",
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        "issn": "2618-6446",
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        "doi": null,
        "doi_prefix": null,
        "slug": "setsci-volume-1-2017-legacy-1",
        "public_id": "1ecf7302-3692-408b-b680-50001a9ab62c",
        "url": "https://www.set-science.com/p/setsci-volume-1-2017-legacy-1"
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        "name": "CC BY 4.0",
        "url": "https://creativecommons.org/licenses/by/4.0/",
        "code": "CC-BY-4.0",
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    "copyright": {
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        "year": "2017"
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        "published": "2017-12-08"
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