GENETIC SYNDROME DETECTION USING RADON TRANSFORM AND BIT PLANES

Genetic syndromes develop different symptoms. One of the commonly observed symptoms is facial dysmorphisms. Hence syndromes may be detected based on facial images. This paper proposes a Radon transform based method for detection of facial dysmorphism. Detection results were improved using bit plane slice approach. Most significant four bit planes of Radon transformed image are proposed to be used for feature extraction. Linear Discriminant Classifier (LDC) and Quadratic Discriminant classifier (QDC) were used for classification. Comparing the results of Radon transform and Radon transform and bit plane slicing, it is observed that accuracy is more by 2.71% using QDC and 10.81% using LDC in later case.