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Automatic Image Segmentation Using Marker Controlled Watershed and Overlap Ratio Based Region Merging
http://hdl.handle.net/20.500.12678/0000007705
http://hdl.handle.net/20.500.12678/00000077054c9d89d0-6e9a-4066-b9c6-573546209e80
3e561e4d-d0a1-4777-a3fe-f21319c533e3
Name / File | License | Actions |
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Publication type | ||||||
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Conference paper | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Automatic Image Segmentation Using Marker Controlled Watershed and Overlap Ratio Based Region Merging | |||||
Language | en | |||||
Publication date | 2018-10-11 | |||||
Authors | ||||||
Khin Lay Mon | ||||||
Su Su Hlaing | ||||||
Mie Mie Tin | ||||||
Mie Mie Khin | ||||||
Description | ||||||
This system intends to produce the correct, useful and meaningful segmented results for medical analyzing tasks, objects detection and recognition in an image. It is tested on two different kinds of datasets: medical images and color natural image dataset. This system has also achieved accuracy 93.01% for MRI brain images, 76.72% for color natural images. |
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Keywords | ||||||
Marker-controlled watershed, Gradient, Region Merging, Over-segmentation | ||||||
Conference papers | ||||||
IEEE GCCE | ||||||
Oct-11/2018 | ||||||
2018 IEEE 7th Global Conference on Consumer Electronic (GCCE 2018) | ||||||
Session 8 (pp-336-346) | ||||||
Japan | ||||||
Techno-Scientific Progress, Climate Change and the Energy Transition for Development |