NSCT BASED LOCAL ENHANCEMENT FOR ACTIVE CONTOUR BASED IMAGE SEGMENTATION APPLICATION

ICTACT Journal on Image and Video Processing ( Volume: 1 , Issue: 1 )

Abstract

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Because of cross-disciplinary nature, Active Contour modeling techniques have been utilized extensively for the image segmentation. In traditional active contour based segmentation techniques based on level set methods, the energy functions are defined based on the intensity gradient. This makes them highly sensitive to the situation where the underlying image content is characterized by image nonhomogeneities due to illumination and contrast condition. This is the most difficult problem to make them as fully automatic image segmentation techniques. This paper introduces one of the approaches based on image enhancement to this problem. The enhanced image is obtained using NonSubsampled Contourlet Transform, which improves the edges strengths in the direction where the illumination is not proper and then active contour model based on level set technique is utilized to segment the object. Experiment results demonstrate that proposed method can be utilized along with existing active contour model based segmentation method under situation characterized by intensity non-homogeneity to make them fully automatic.

Authors

Hiren Mewada, Suprava Patnaik
Sardar Vallbhbhai National Institute of Technology, India

Keywords

Segmentation, Nonsubsampled Contourlet Transform (NSCT), Active Contour Model (AVM)

Published By
ICTACT
Published In
ICTACT Journal on Image and Video Processing
( Volume: 1 , Issue: 1 )
Date of Publication
August 2010
Pages
27 - 31

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