Glaucoma Detection using Wavelet based Contourlet Transform

被引：0
|
作者：
Nirmala, K. [1 ]
Venkateswaran, N. [1 ]
Kumar, Vinoth C. [1 ]
Christobel, Shiny J. [1 ]
机构：
[1] SSN Coll Engn, Chennai, Tamil Nadu, India
来源：
PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL (I2C2) | 2017年
关键词：
Adaptive Gamma Correction with Weighted Distribution Function; Wavelet Based Contourlet Transform; Gabor filter; Morphological operator; Naive Bayes classifier; FEATURE-EXTRACTION; OPTIC DISK; TEXTURE; IMAGES;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
One of the leading retinal diseases which cause vision loss is Glaucoma. This paper presents the methodology to detect Glaucoma using wavelet based contourlet transform with Gabor filters. The input retinal fundus image is localized for its region of interest and enhanced using adaptive Gamma correction with weighted Distribution function (AGCWD). The blood vessels in ROI are removed using the Gabor filter and morphological operators. To the Region of Interest the wavelet based contourlet transform (WBCT) is applied to extract the features and then given to the Naive Bayes (NB) classifiers for detecting the normal and glaucomatous image.
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页数：5
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