TY  - JOUR
T1  - Particle Swarm Optimization-Based Thresholding for Corneal Segmentation in Pterygium Detection
AU - Abdani, Siti Raihanah AU - W. Zaki, W. Mimi Diyana AU - Hussain, Aini AU - Md. Saad, Mohamad Hanif 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 11
SP  - 1845
EP  - 1850
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.1845.1850
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.1845.1850
KW  - Pterygium
KW  -ASPI
KW  -particle swarm optimization
KW  -frame
KW  -accuracy
AB  - Pterygium tends to affect those who are exposed to prolonged uv radiation in which Asian people are more susceptible to develop such condition. Thus, a computerized method that can automatically detect pterygium is greatly needed and is being proposed using image processing approach. The main focuses of this researchers is corneal segmentation of eye region in the Anterior Segment Photographed Images (ASPI). A heuristic approach based on Particle Swarm Optimization (PSO) thresholding is explored to segment the corneal to further improve the segmentation rate of non-ideal images that contain pterygium condition. To obtain the corneal after applying PSO, the three steps thresholding method is used based on frame differencing between multi color channels (HSV). Brazil Pterygium (BP) database is used to represent the pterygium condition while UBIRIS.V<SUB>1</SUB>, UBIRIS.V<SUB>2</SUB> and Miles databases are used to represent the normal eye condition. Both pterygium and normal ASPIs have been tested rigorously to validate the robustness of the proposed algorithm. The results showed that BP have the highest accuracy (94%) while UBIRIS.V<SUB>1</SUB> have the highest accuracy (93.2%) for the non pterygium database. In conclusion, it shows that the proposed method is mostly suitable for application in Asian countries in which there is increasing trend of pterygium cases.
ER  -