DocumentCode
238532
Title
Analysis and performance evaluation of various image segmentation methods
Author
Mageswari, S. Umaa ; Mala, C.
Author_Institution
Comput. Sci. & Eng. Dept., Nat. Inst. of Technol., Tiruchirappalli, India
fYear
2014
fDate
27-29 Nov. 2014
Firstpage
469
Lastpage
474
Abstract
Image segmentation is a primary stage in image processing for identifying objects of interest. Segmentation methods are classified into region based, transform based, edge based and clustering based segmentation. In this paper, segmentation methods including histogram, watershed, Canny edge detector and K-means clustering techniques are studied and analyzed. The experimental results obtained are compared with different evaluation measures including three standard image segmentation indices: rand index, globally consistency error and variation of information.
Keywords
image classification; image segmentation; transforms; Canny edge detector; clustering based segmentation; edge based segmentation; histogram; image segmentation methods; k-means clustering technique; region based segmentation; transform based segmentation; watershed; Detectors; Histograms; Image color analysis; Image edge detection; Image reconstruction; Image segmentation; Mathematical model;
fLanguage
English
Publisher
ieee
Conference_Titel
Contemporary Computing and Informatics (IC3I), 2014 International Conference on
Conference_Location
Mysore
Type
conf
DOI
10.1109/IC3I.2014.7019614
Filename
7019614
Link To Document