DocumentCode
2347941
Title
A Review on the Strategies and Techniques of Image Segmentation
Author
Bali, Akanksha ; Singh, Shailendra Narayan
Author_Institution
Comput. Sci. & Eng. Dept., Amity Univ., Noida, India
fYear
2015
fDate
21-22 Feb. 2015
Firstpage
113
Lastpage
120
Abstract
Segmentation is a method of partitioning an image or picture into different regions which has same attributes like Texture, intensity, gray level etc with the motive to yield object of interest from the background. It is a method in which we included the object belongs to the same category in one class and the objects that belong to other category are added in other class for separating the object and background. There are several image segmentation techniques namely traditional thresholding (Otsu) and clustering segmentation (K-means). By differentiating all these image segmentation techniques we have to find which segmentation technique is better on the characteristics of image segmented. Segmentation is done on built in environment which becomes more demanding. In built in environment, both K-means and Otsu are unsuccessful to yield good standard of segmentation because of varying lightening on the image and complex surrounding.
Keywords
image segmentation; image texture; pattern clustering; K-means clustering segmentation; Otsu thresholding; complex surrounding; gray level attribute; image background; image lightening; image partitioning; image segmentation; intensity attribute; object category; objects class; picture partitioning; texture attribute; Clustering algorithms; Histograms; Image color analysis; Image edge detection; Image segmentation; Merging; Partitioning algorithms; K-means; Otsu; Synthetic aperture radar (SAR); Thresholding; Ultrasound images; expectation maximization; neural network; wavelength decomposition;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computing & Communication Technologies (ACCT), 2015 Fifth International Conference on
Conference_Location
Haryana
Print_ISBN
978-1-4799-8487-9
Type
conf
DOI
10.1109/ACCT.2015.63
Filename
7079063
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