Spinal deformity is one of serious disease and it is mainly suffer by teenagers during their growth stage particularly fifth year in the elementary school to second year in the middle school. To detect the spinal deformity, medical doctors check a large number of moire images for mass screening. Therefore realization of automated spinal deformity inspection based on the moire images has long been desired among orthopedists. In this paper, we propose a new method for spinal deformity detection based on four statistical features from the difference of symmetric degree on moire topographic images. We perform the proposed technique to 1200 real moire images in the classification employing Artificial Neural Networks and Support Vector Machines. The method can classify as normal or abnormal from the moire topographic images automatically.
