SEGMENTASI AREA GIGI MENGGUNAKAN FUZZY C-MEANS

Abstract

Researches with early detection of caries using x-ray topic has been widely developed, generally before doing object detection, the early step is segmentation. Image segmentation is one of the digital image processing steps used to segregate an area or object observed with other areas or objects. Segmentation has an important role as the initial determination of the desired area or object so that it can be continued to the identification stage. FCM (fuzzy c-means) algorithm is one of object segmentation technique or object grouping in the field of digital image processing study. The basic concept of FCM is to determine the centroid and members of each group adaptively, in principle FCM uses a fuzzy grouping model so that a data or element becomes a member of all the clusters that are formed.

Segmentation of the dental area using FCM with 4 clusters aims to segment the enamel, dentin, pulp, and backround areas. The result of segmentation using FCM is influenced by the condition of the dataset used. The background area of the entire dataset can be well segmented. FCM is also capable of segmenting the enamel area but in some datasets, the enamel segmentation results are still mixed with other teeth areas. For the dentin and pulp areas, the segmentation result of these two areas is not optimal yet; most of the dentin and or pulp areas are still segmented with the other teeth’s area.