ITE Technical Group Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2016-08-26 15:20
Automated retinal blood vessel extraction based on black-hat transformation and high-order local autocorrelation
Yuji Hatanaka, Kazuki Samo, Kazunori Ogohara (Univ. Shiga Prefecture), Chisako Muramatsu (Gifu Univ.), Wataru Sunayama (Univ. Shiga Prefecture), Hiroshi Fujita (Gifu Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) An automated blood vessel extraction using high-order local autocorrelation (HLAC) on retinal images is presented. The blood vessels were enhanced by black-hat transformation as a pre-processing. One hundred five HLAC features were calculated in a black-hat filtered image, and they were inputted into a first layer of an artificial neural network (ANN). The output, a green component of the color retinal image, output values of three kinds of filter were then inputted into a second layer of ANN. Using DRIVE database, the area under the curve (AUC) based on ROC analysis was 0.960 as a result of our study. The result can be used for the blood vessels extraction.
Keyword (in Japanese) (See Japanese page) 
(in English) Blood vessel extraction / High-order local autocorrelation / Hypertensive change / Retinal image / Segmentation / / /  
Reference Info. ITE Tech. Rep., vol. 40, pp. 27-30, Aug. 2016.
Paper #  
Date of Issue 2016-08-19 (AIT) 
ISSN Print edition: ISSN 1342-6893    Online edition: ISSN 2424-1970
Download PDF

Conference Information
Committee AIT IIEEJ  
Conference Date 2016-08-26 - 2016-08-26 
Place (in Japanese) (See Japanese page) 
Place (in English) FUTURE UNIVERSITY HAKODATE 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IIEEJ 
Conference Code 2016-08-AIT-IIEEJ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automated retinal blood vessel extraction based on black-hat transformation and high-order local autocorrelation 
Sub Title (in English)  
Keyword(1) Blood vessel extraction  
Keyword(2) High-order local autocorrelation  
Keyword(3) Hypertensive change  
Keyword(4) Retinal image  
Keyword(5) Segmentation  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Yuji Hatanaka  
1st Author's Affiliation University of Shiga Prefecture (Univ. Shiga Prefecture)
2nd Author's Name Kazuki Samo  
2nd Author's Affiliation University of Shiga Prefecture (Univ. Shiga Prefecture)
3rd Author's Name Kazunori Ogohara  
3rd Author's Affiliation University of Shiga Prefecture (Univ. Shiga Prefecture)
4th Author's Name Chisako Muramatsu  
4th Author's Affiliation Gifu University (Gifu Univ.)
5th Author's Name Wataru Sunayama  
5th Author's Affiliation University of Shiga Prefecture (Univ. Shiga Prefecture)
6th Author's Name Hiroshi Fujita  
6th Author's Affiliation Gifu University (Gifu Univ.)
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Speaker Author-1 
Date Time 2016-08-26 15:20:00 
Presentation Time 25 minutes 
Registration for IIEEJ 
Paper # AIT2016-144 
Volume (vol) vol.40 
Number (no) no.27 
Page pp.27-30 
#Pages
Date of Issue 2016-08-19 (AIT) 


[Return to Top Page]

[Return to ITE Web Page]


The Institute of Image Information and Television Engineers (ITE), Japan