NDLI: Image Segmentation Based on Moments and Color Map

Content Provider	IEEE Xplore Digital Library
Author	Ashtputre, S. Sharma, M. Ramaiya, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Eng., ShriRam Coll. Of Eng.& Mgmt, Gwalior, India (Ashtputre, S.; Sharma, M.; Ramaiya, M.)
Abstract	Image segmentation is to identify homogenous regions in the image. Basically, the main role of image segmentation is to cluster pixels into prominent image regions i.e. the regions which are corresponding to individual surfaces, objects or natural parts of the objects. The moment is an invariant feature which has been used for object recognition as a descriptor. Additionally, color map can also be used for clustering pixels in corresponding region. In this paper color map is used as a feature for clustering purpose. Color map is obtained by finding out labels in an image. For each possible window representation of each pixel in an image, statistical moment values are computed. Now feature vector of each pixel is then classified using k-means clustering method. Quantitative analysis is done to show the accuracy of the used feature vector i.e. moments and color-map.
Sponsorship	IEEE India Council MTT Chapt.
Starting Page	133
Ending Page	136
File Size	207824
Page Count	4
File Format	PDF
ISBN	9781467356039
e-ISBN	9781467356039
DOI	10.1109/CSNT.2013.37
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-06
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Color-map Image segmentation Accuracy Color moments Image color analysis Noise Support vector machine classification Clustering algorithms Object recognition K-mean
Content Type	Text
Resource Type	Article

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