Image segmentation is in fact one of the most fundamental approach of digital image processing. In image processing, segmentation playa an important role. It may be defined as partitioning an image into meaning full regions or objects. In other words we can say that process of segmentation keeps on dividing an image into its constitute sub parts. The level to which the subdivision is carried on depends on type of problem to be solved by researchers. This segmentation process continues unless area of interest is isolated. Set of segment or set of contours that are extracted from the image is the main result of image segmentation. There are various application of image segmentation like locating tumors or other pathologies, measuring tissue volume, surgery aided by computer, treatment and planning, study of various anatomical structure, locating objects in satellite images, fingerprint. There are various types of generalized algorithm and methodology that are developed for image segmentation. Some common technique of image segmentation such as edge detection, thresh holding, region growing and clustering are taken for this study. In fact segmentation algorithm are based on two properties similarity and discontinuity. This paper concentrates on the various methods that are widely used to segment the image.
| Published in | American Journal of Computer Science and Technology (Volume 2, Issue 4) |
| DOI | 10.11648/j.ajcst.20190204.14 |
| Page(s) | 68-72 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2019. Published by Science Publishing Group |
Segmentation, Digital Image Processing, Edge Detection, Thres Holding, Region Growing, Clustering
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APA Style
Puja Shashi, Suchithra R. (2019). Review Study on Digital Image Processing and Segmentation. American Journal of Computer Science and Technology, 2(4), 68-72. https://doi.org/10.11648/j.ajcst.20190204.14
ACS Style
Puja Shashi; Suchithra R. Review Study on Digital Image Processing and Segmentation. Am. J. Comput. Sci. Technol. 2019, 2(4), 68-72. doi: 10.11648/j.ajcst.20190204.14
AMA Style
Puja Shashi, Suchithra R. Review Study on Digital Image Processing and Segmentation. Am J Comput Sci Technol. 2019;2(4):68-72. doi: 10.11648/j.ajcst.20190204.14
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Download@article{10.11648/j.ajcst.20190204.14,
author = {Puja Shashi and Suchithra R},
title = {Review Study on Digital Image Processing and Segmentation},
journal = {American Journal of Computer Science and Technology},
volume = {2},
number = {4},
pages = {68-72},
doi = {10.11648/j.ajcst.20190204.14},
url = {https://doi.org/10.11648/j.ajcst.20190204.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20190204.14},
abstract = {Image segmentation is in fact one of the most fundamental approach of digital image processing. In image processing, segmentation playa an important role. It may be defined as partitioning an image into meaning full regions or objects. In other words we can say that process of segmentation keeps on dividing an image into its constitute sub parts. The level to which the subdivision is carried on depends on type of problem to be solved by researchers. This segmentation process continues unless area of interest is isolated. Set of segment or set of contours that are extracted from the image is the main result of image segmentation. There are various application of image segmentation like locating tumors or other pathologies, measuring tissue volume, surgery aided by computer, treatment and planning, study of various anatomical structure, locating objects in satellite images, fingerprint. There are various types of generalized algorithm and methodology that are developed for image segmentation. Some common technique of image segmentation such as edge detection, thresh holding, region growing and clustering are taken for this study. In fact segmentation algorithm are based on two properties similarity and discontinuity. This paper concentrates on the various methods that are widely used to segment the image.},
year = {2019}
}
TY - JOUR T1 - Review Study on Digital Image Processing and Segmentation AU - Puja Shashi AU - Suchithra R Y1 - 2019/12/31 PY - 2019 N1 - https://doi.org/10.11648/j.ajcst.20190204.14 DO - 10.11648/j.ajcst.20190204.14 T2 - American Journal of Computer Science and Technology JF - American Journal of Computer Science and Technology JO - American Journal of Computer Science and Technology SP - 68 EP - 72 PB - Science Publishing Group SN - 2640-012X UR - https://doi.org/10.11648/j.ajcst.20190204.14 AB - Image segmentation is in fact one of the most fundamental approach of digital image processing. In image processing, segmentation playa an important role. It may be defined as partitioning an image into meaning full regions or objects. In other words we can say that process of segmentation keeps on dividing an image into its constitute sub parts. The level to which the subdivision is carried on depends on type of problem to be solved by researchers. This segmentation process continues unless area of interest is isolated. Set of segment or set of contours that are extracted from the image is the main result of image segmentation. There are various application of image segmentation like locating tumors or other pathologies, measuring tissue volume, surgery aided by computer, treatment and planning, study of various anatomical structure, locating objects in satellite images, fingerprint. There are various types of generalized algorithm and methodology that are developed for image segmentation. Some common technique of image segmentation such as edge detection, thresh holding, region growing and clustering are taken for this study. In fact segmentation algorithm are based on two properties similarity and discontinuity. This paper concentrates on the various methods that are widely used to segment the image. VL - 2 IS - 4 ER -
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