Cite this DOI

Kumar, K. N., Kartheek, G. L. N. V., & Prasad, G. V. S. C. S. L. V. (2021). Image Segmentation using Extended Edge Operatorfor Mammographic Images. *Journal of Science & Technology*, *06*(06), 174–179. https://doi.org/10.46243/jst.2021.v6.i06.pp174-179

@article{kumar2021image,
  author    = {Kumar, K Naresh and Kartheek, G L N V and Prasad, G V S Ch S L V},
  title     = {{Image Segmentation using Extended Edge Operatorfor Mammographic Images}},
  journal   = {Journal of Science \& Technology},
  year      = {2021},
  volume    = {06},
  number    = {06},
  pages     = {174--179},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2021.v6.i06.pp174-179},
  url       = {https://doi.org/10.46243/jst.2021.v6.i06.pp174-179},
  language  = {en},
  abstract  = {Detection of edges in an image is a very important step towards understanding image features. Since edges oftenoccur at image locations representing object boundaries, edge detection is extensively used in image segmentation when images are divided into areas corresponding to different objects. This can be used specifically for enhancing the tumor area in mammographic images. In this paper extended Sobel , Prewitt and Kirsch edge operators are proposed for image segmentation of mammographic images. Edges and tumor location can be seen clearly by using this method. For comparison purpose Gray level co-occurrence matrix, watershed algorithm, present Sobel, Prewitt and Kirsch edge operators are used and their results are displayed.}
}

TY  - JOUR
TI  - Image Segmentation using Extended Edge Operatorfor Mammographic Images
AU  - Kumar, K Naresh
AU  - Kartheek, G L N V
AU  - Prasad, G V S Ch S L V
JO  - Journal of Science & Technology
PY  - 2021
DA  - 2021///
VL  - 06
IS  - 06
SP  - 174
EP  - 179
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - Detection of edges in an image is a very important step towards understanding image features. Since edges oftenoccur at image locations representing object boundaries, edge detection is extensively used in image segmentation when images are divided into areas corresponding to different objects. This can be used specifically for enhancing the tumor area in mammographic images. In this paper extended Sobel , Prewitt and Kirsch edge operators are proposed for image segmentation of mammographic images. Edges and tumor location can be seen clearly by using this method. For comparison purpose Gray level co-occurrence matrix, watershed algorithm, present Sobel, Prewitt and Kirsch edge operators are used and their results are displayed.
DO  - 10.46243/jst.2021.v6.i06.pp174-179
UR  - https://doi.org/10.46243/jst.2021.v6.i06.pp174-179
ER  -

{
    "type": "article-journal",
    "id": "10.46243/jst.2021.v6.i06.pp174-179",
    "DOI": "10.46243/jst.2021.v6.i06.pp174-179",
    "URL": "https://doi.org/10.46243/jst.2021.v6.i06.pp174-179",
    "title": "Image Segmentation using Extended Edge Operatorfor Mammographic Images",
    "source": "Smart Scholars DOI Registry",
    "container-title": "Journal of Science & Technology",
    "author": [
        {
            "family": "Kumar",
            "given": "K Naresh"
        },
        {
            "family": "Kartheek",
            "given": "G L N V"
        },
        {
            "family": "Prasad",
            "given": "G V S Ch S L V"
        }
    ],
    "issued": {
        "date-parts": [
            [
                2021
            ]
        ]
    },
    "volume": "06",
    "issue": "06",
    "page": "174-179",
    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "Detection of edges in an image is a very important step towards understanding image features. Since edges oftenoccur at image locations representing object boundaries, edge detection is extensively used in image segmentation when images are divided into areas corresponding to different objects. This can be used specifically for enhancing the tumor area in mammographic images. In this paper extended Sobel , Prewitt and Kirsch edge operators are proposed for image segmentation of mammographic images. Edges and tumor location can be seen clearly by using this method. For comparison purpose Gray level co-occurrence matrix, watershed algorithm, present Sobel, Prewitt and Kirsch edge operators are used and their results are displayed.",
    "ISSN": "2456-5660"
}

From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2021.v6.i06.pp174-179 gives all four in one JSON answer.