Title :
A binary-segmentation algorithm based on shearlet transform and eigenvectors
Author :
Sharafyan Cigaroudy, Ladan ; Aghazadeh, Nasser
Author_Institution :
Dept. of Appl. Math., Azarbaijan Shahid Madani Univ., Tabriz, Iran
Abstract :
In this paper, we illustrate an iterative algorithm for extraction of object with tubular structure specially vessel extraction. For this aim, we segment image to reach binary image in which the pixels of purpose object is found. In our segmentation method, we use Gaussian scale-space technique to compute discrete gradient of image for pre-segmenting. Also, in order to denoise, we use tight frame of shearlet transform. This algorithm has an iterative part based on iterative part of TFA [2], but we use eigenvectors of Hessian matrix of image for improving this part. Theoretical properties of this method are presented. The experimental results show that in our algorithm distinguishing homogeneous vessels is done efficiently.
Keywords :
Gaussian processes; Hessian matrices; blood vessels; eigenvalues and eigenfunctions; feature extraction; image denoising; image segmentation; iterative methods; medical image processing; transforms; Gaussian scale-space technique; Hessian matrix; binary image; binary-segmentation algorithm; discrete gradient; eigenvectors; homogeneous vessels; image denoising; image segmentation; iterative algorithm; object extraction; shearlet transform; tubular structure; vessel extraction; Image segmentation; Shearlets; eigen vector; thresholding; tubular structure;
Conference_Titel :
Pattern Recognition and Image Analysis (IPRIA), 2015 2nd International Conference on
Conference_Location :
Rasht
Print_ISBN :
978-1-4799-8444-2
DOI :
10.1109/PRIA.2015.7161618
