Caries Detection Technique for Radiographic and Intra Oral Camera Images
Adhar Vashishth1, Bipan Kaushal2, Abhishek Srivastava3
1Adhar Vashishth, Department of Electronics and Communication Engineering, PEC University of Technology, Chandigarh, India.
2Prof. Bipan Kaushal, Department of Electronics and Communication Engineering, PEC University of Technology, Chandigarh, India.
3Abhishek Srivastava, Department of Electronics and Communication Engineering, PEC University of Technology, Chandigarh, India.
Manuscript received on May 01, 2014. | Revised Manuscript received on May 05, 2014. | Manuscript published on May 05, 2014. | PP: 188-190 | Volume-4 Issue-2, May 2014. | Retrieval Number: B2254054214/2014©BEIESP
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©The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: In the modern times, caries is one of the most prevelent disease of the teeth in the whole world. A large percentage of population is affected by them. Dentists try their level best to identify the problem at an earlier stage, but, with poor dentist to patient ratio , the problem becomes compounded. To provide them a helping hand various machines and techniques are developed. Prominent among them is the DIFOTI(digital imaging fiber-optic transillumination) technique, but it requires very expensive machinery to work with which can not be afforded by most of the dentists. We are proposing a method that can provide the needed diagnostic help without requiring the kind of machinery currently in use. We have used image processing technique to identify the caries that provide the dentists with the precise results about caries and the area affected. This method can detect caries in radiographic images as well as in intra oral camera images. This will not only help in countering the low man power problem but will also provide an accurate and cost effective method in identifying and treating caries.
Keywords: Binarization, caries, mask, RGB plane, MATLAB.