Abstract:
Now a days identifying skin diseases clinically is not an easy task. Jaundice is one of them.
Jaundice which is also known as icterus is yellowish discolouration of skin and mucous
membranes due to accumulation of bile pigments (bilirubin) in blood and deposition in
body tissues. Skin and white part of the eyes (sclera) gets yellowish appearance due to a
yellow pigment. With clinical exposure doctors usually diagnose jaundice by identifying
the yellowish tinge of palms and sclera in general examination if it is present. Identifying
the discoloration clinically is differed according to person’s level of vision. And
sometimes it is difficult to clearly identify the yellowing in the dark skins especially in
south Asian countries. When strong Jaundice is presented, babies or adults should be
subject to clinical exam like "serum bilirubin" which can cause traumas in patients, And
also there are some invasive tests has to be done by the doctors to identify the cause of the
jaundice.
Many researchers have been developed some different algorithms to detect jaundice.
Some are still using an invasive methods at least once for the beginning and some are not
directly check the skin and sclera colours. In this project, new algorithmic approach is
introduced to identify the jaundice symptoms using images of the patient and analyzing
the image. The new approach is mainly based on the patients in south Asian countries.
