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Automatic Approach for Detection of Abnormality within MRI Dental Images Using Gaussian Filtering and SVM Hybridization

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  • Sharanjit Kaur
  • Navjot Kaur

Abstract

Dental care is state of the art problem which must be detected at early stage in order to overcome severities. To tackle the problem proposed system uses multiple techniques present within image processing and hybridized it. Proposed system uses pre-processing is performed to improve quality of images using modified Gaussian filtering, feature extraction process is performed in order to determine critical and non-critical segments, morphological filtering mechanism is applied to determine the teeth ends to be classified properly and support vector machine is applied to classify the disease to appropriate class. Results are obtained in terms of classification accuracy and mean square error. Overall simulation is conducted within MATLAB 2017 and result is 99% in terms of accuracy.

Suggested Citation

  • Sharanjit Kaur & Navjot Kaur, 2018. "Automatic Approach for Detection of Abnormality within MRI Dental Images Using Gaussian Filtering and SVM Hybridization," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 3(5), pages 326-334, June.
    • Handle: RePEc:jbh:ijsrcs:v3:y2018:i5:id:hcseit183571
    Note: Article URL: https://ijsrcseit.com/CSEIT183571
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