PARAMETER SIGMOID TRANSFORM CONTRAST ENHANCEMENT FOR DENTAL RADIOGRAPH CLASSIFICATION AND NUMBERING SYSTEM

Abstract

Dental record is a method that is used to identify a person. The identification process needs a system that could recognize each individual tooth automatically. The similar intensity level between the teeth and the gums is one of the main problem in tooth identification in a dental radiograph. The intensity problem could influence the segmentation process of the system. In this paper, we proposed a new contrast enhancement by using parameter sigmoid transform to increase the segmentation accuracy. There are five main steps in this method. The first step is to fix the contrast of the image with the proposed method. The next steps are to segment the teeth using horizontal and vertical integral projection, feature extraction, and classification using Support Vector Machine (SVM). The last step is teeth numbering. The experiment result using the proposed method have an accuracy rate of 88% for classification and 73% for teeth numbering.