Title :
Segmentation of blurred images using improved Chan-Vese snake model
Author :
Reddy, G. Ramachandra ; Chandra, M.M. ; Rao, Rohini R.
Author_Institution :
Dept. of ECE, KITS, Warangal, India
Abstract :
Accurately extracting the features of interest from a blurred image is one of the difficult tasks in image segmentation. This paper uses the blind deconvolution, deblurring algorithm to find original features of interest, and then uses the improved Chan Vese snake model to get the accurate features. The presented algorithm is tested on the MRI images of brain and results are found to be satisfactorily.
Keywords :
deconvolution; feature extraction; image segmentation; Chan-Vese snake model; MRI image; blind deconvolution; blurred image segmentation; deblurring algorithm; feature extraction; magnetic resonance imaging; Active contours; Computational modeling; Deconvolution; Image edge detection; Image segmentation; Mathematical model; Signal processing algorithms; Active Contour; Blind Deconvolution; CV model; Deblurring; Image Segmentation;
Conference_Titel :
Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), 2011 International Conference on
Conference_Location :
Thuckafay
Print_ISBN :
978-1-61284-654-5
DOI :
10.1109/ICSCCN.2011.6024603
