Abstract
Down syndrome is one of the genetic disorders that usually happened to the humans. Children born with Down syndrome may have a delay in physical growth and a particular set of facial characteristics because of the presence of an extra 21st chromosome. In order to diagnose the patient with Down syndrome, a chromosomal test can be done to check for the extra chromosome and confirm the diagnosis. However, the testing consumes a large amount of time and money. Therefore, we want to develop a method to recognize the child with Down syndrome in a simple and fast way. As mentioned before, patients with Down syndrome usually have multiple abnormal facial features. Therefore, we can develop a disease recognition system with the facial characteristics to help doctors examine the patient. By inputting the photo, including lateral and frontal face of the patient, into our proposed system, the important facial features of Down syndrome can be extracted. After the extraction, the features will be inputted into the classification system, with a recognized model trained before. The system can discriminate between the person with Down syndrome and normal one by the trained model. Hence, we can recognize the child with Down syndrome. We select the eight important facial features that usually happen to the patient with Down syndrome. The characteristics are as follows: hypertelorism, almond eyes, up-slanting palpebral fissures, up-turned nose, flat nasal bridge and low-set ears. Experimental results show that the accuracy rate of our disease recognition system is nearly 90% to recognize Down syndrome case correctly.