A review—Edge detection techniques in dental images

Abstract

Edge detection plays an important role in digital image processing applications. The main aim of edge detection is to identify the discontinuity in images, where the sharp changes in intensity take place. This research work presents the edge detection technique in dental X-ray images (panoramic radiograms), which is advantageous to separate teeth individually for better classification and identification of diseases. The objective is to study and compare the various algorithms that are Sobel, Prewitt, Canny, multiple morphological gradient (mMG), line analyzer, neural network, genetic algorithm, and infinite symmetric filter (ISF), multi-scale and multi-directional analysis with statistical thresholding (MMST), and fuzzy logic approach for edge detection in dental X-ray images. There are many difficulties in finding diseases from panoramic dental images only, and hence to overcome these difficulties edge detection is introduced. Some of the dental diseases that require edge detection for their identification are discussed. Based on capability of detecting the diseases accurately and total number of diseases detected from the dental images by the use of edge detection, comparison of results takes place.