Malays. Appl. Biol. (2018) 47(2): 47–52
AUTOMATIC BLOOD VESSEL DETECTION ON RETINAL IMAGE
USING HYBRID COMBINATION TECHNIQUES
WAN AZANI MUSTAFA* and MOHAMED MYDIN M. ABDUL KADER
Faculty of Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus,
Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
*E-mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it
Accepted 25 April 2018, Published online 25 May 2018
ABSTRACT
A blood vessel in the retinal is one of the important organs especially to diagnose diseases such as diabetic retinopathy and glaucoma. In this study, a new method for automatic segmentation of blood vessels in retinal images was presented. The proposed method is based on a hybrid combination between Gray-Level and Moment Invariant techniques. There are consists four stages of processing, (1) preprocessing, (2) feature extraction, (3) classification, and (4) post-processing. The proposed method was compared to the Vascular Tree and Morphological method. Based on the objective evaluation, the proposed method successfully achieved a sensitivity of 98.589% and specificity of 55.544% compared to the others.
Key words: Automatic, segmentation, retinal, gray-level, moment invariant
