Browse > Article
http://dx.doi.org/10.6109/jkiice.2014.18.12.3029

Scleral Diagnostic System Implementation with Color and Blood Vessel Sign Pattern Code Generations  

Ryu, Kwang Ryol (Department of Electronic Engineering, Mokwon University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.12, 2014 , pp. 3029-3034 More about this Journal
Abstract
The paper describes the scleral diagnostic system implementation for human eyes by using the scleral color code and vessels sign pattern code generations. The system is based on the high performance DSP image signal processor, programmable gain control for preprocessing and RISC SD frames storage. RGB image signals are optimized by PGC, the edge image is detected form the gray image converted. The processing algorithms are executed by scleral color code generation and scleral vessels sign pattern code creation for discriminating and matching. The scleral symptomatic color code is generated by YCbCr values at memory map tolerated and the vessel sign pattern code is created by digitizing the 24 clock and 13 ring zones, overlay matching and tolerances. The experimental results for performance are that the system runs 40ms, and the color and pattern for diagnostic errors are around 20% and 24% on average. The system and technique enable a scleral diagnosis with subdividing the patterns and patient database.
Keywords
Scleral diagnostic system; Scleral color code; Scleral blood vessels sign pattern code;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Shreelekshmi et al, "Human Identification Based on Pattern of Blood Vessels as Viewed on Sclera Using HOG and Interpolation Technique", Intn'l J. of Adv. Research in Computer Sci. and Mgr. Studies, vol.2, issue.9, 2014.
2 Donald R. Bamer, Practical Iridology and Sclerology, Woodland Publishing, 1996.
3 Richard P. Wildes, Recognition: An Emerging Biometric Technology", proceedings of the IEEE, vol.85, no.9, pp.1348-1363, September 1997.   DOI   ScienceOn
4 Christel-Loic Tisse, Lionel Martin, Lionel Torres and Michel" Robert, "Person Identification Technique using Human Iris Recognition", Proc. of the 15th Int. Conf. on Vision Interface, 2002.
5 Kwang Ryol Ryu, "Iris Pattern positioning with preserved Edge Dectector and Overlay Matching", International Journal of KIMICS, vol.8, no.3. pp.339-342, Jun. 2010.
6 Simona Crihalmeanu, Arun Ross, "Multispectral Scleral Patterns for Ocular Biometric Recognition", West Virginia Univ., Pattern Recognition Letters 33, pp. 1860-1869, 2012.   DOI   ScienceOn