@article{(Open Science Index):https://publications.waset.org/pdf/10010012,
	  title     = {Analysis of Image Segmentation Techniques for Diagnosis of Dental Caries in X-ray Images},
	  author    = {V. Geetha and  K. S. Aprameya },
	  country	= {},
	  institution	= {},
	  abstract     = {Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {13},
	  number    = {2},
	  year      = {2019},
	  pages     = {30 - 33},
	  ee        = {https://publications.waset.org/pdf/10010012},
	  url   	= {https://publications.waset.org/vol/146},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 146, 2019},
	}