Content-based automatic retinal image recognition and retrieval system / 生物医学工程学杂志
Journal of Biomedical Engineering
; (6): 403-408, 2013.
Article
in Zh
| WPRIM
| ID: wpr-234641
Responsible library:
WPRO
ABSTRACT
This paper is aimed to fulfill a prototype system used to classify and retrieve retinal image automatically. With the content-based image retrieval (CBIR) technology, a method to represent the retinal characteristics mixing the fundus image color (gray) histogram with bright, dark region features and other local comprehensive information was proposed. The method uses kernel principal component analysis (KPCA) to further extract nonlinear features and dimensionality reduced. It also puts forward a measurement method using support vector machine (SVM) on KPCA weighted distance in similarity measure aspect. Testing 300 samples with this prototype system randomly, we obtained the total image number of wrong retrieved 32, and the retrieval rate 89.33%. It showed that the identification rate of the system for retinal image was high.
Full text:
1
Index:
WPRIM
Main subject:
Ophthalmoscopy
/
Pathology
/
Reference Standards
/
Retina
/
Retinal Vessels
/
Algorithms
/
Image Processing, Computer-Assisted
/
Numerical Analysis, Computer-Assisted
/
Pattern Recognition, Automated
/
Information Storage and Retrieval
Limits:
Humans
Language:
Zh
Journal:
Journal of Biomedical Engineering
Year:
2013
Type:
Article