User Interactive Image Segmentation for Efficient Image Database Indexing

Author(s):

Anjali Ananthan , THEJUS ENGINEERING COLLEGE; R Jayadevan, Government Engineering College,Thrissur; Mahesh K.R, Thejus Engineering College,

Keywords:

Feature extraction, Indexing, Manhattan distance, Mean shift clustering, Merging, Neighbourhood Classification, Pruning, User interactive segmentation

Abstract:

This paper is mainly focussing on the area image database indexing. For this purpose a user interactive image segmentation algorithm is applied to the input image. After performing segmentation of the input image only the desired portion of the image i.e., the foreground is extracted. Interactive segmentation stage is followed by a feature extraction process that is performed for the image database as well as the region database. The features extracted include some colour features and texture features. Then using Manhattan distance a similarity measurement is done for images under same concept as well as images under different concept for both images in database as well as well as for segmented regions. It is found that user interactive image segmentation proves to be a very efficient method of indexing of image database.

Other Details:

Manuscript Id	:	IJSTEV1I11122
Published in	:	Volume : 1, Issue : 11
Publication Date	:	01/06/2015
Page(s)	:	323-327

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