• Krishna Kumari S
• Dr.C.Murukesh

The aim of this proposed work is to assess the eye color in conjunctiva using microscope images through Empirical Wavelet Transform (EWT) and compare it with the Neural Network Forward (NNF). Materials and Methods: The assessment was carried out for ten subjects whose eye images were captured using a microscope. Group 1 is considered as EWT, Group 2 is NNF, each consisting of ten samples totaling twenty samples. The number of samples was calculated with a pretest G power of 80 % and an error rate of 0.05. Results: The statistical analysis was done using SPSS, in EWT the average entropy was obtained was 3.5301 which is higher than obtained through NNF 2.9702. Conclusion: Eye color change assessment through novel EWT is significantly better than the NNF algorithm. Within the limitations of this study, tortuosity measurement using the eye through EWT has a higher significance than an NNF.

Conjunctiva, Eye Color Change Assessment, Empirical Wavelet Transform, Neural Network, Tortuosity, Feature extraction.

"Conjunctiva of Eye Colour Change Assessment Using Microscope Image for Improving Tortuosity Through Empirical Wavelet Transform Compared with Neural Network - Forward ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.90-95, June-2019, Available :http://www.jetir.org/papers/JETIR1907W14.pdf

"Conjunctiva of Eye Colour Change Assessment Using Microscope Image for Improving Tortuosity Through Empirical Wavelet Transform Compared with Neural Network - Forward ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp90-95, June-2019, Available at : http://www.jetir.org/papers/JETIR1907W14.pdf