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1R. Kiruthikaa & 2N. Sathiyapriya

1,2Assistant Professor / ECE

Karpagam Institute of Technology

Abstract— In this paper used to improve detection precisions, we propose three post-processing techniques to supplement the baseline faster  R-CNN according to certain prior domain knowledge. Filtering algorithm is constructed to delete overlapping boxes detected by faster R-CNN associated with the same tooth.In this paper already defined for labels in teeth image. The module based on a teeth is proposed to matching for training image and Testing images of detected teeth boxes to modify detected results that violate certain intuitive rules.In this proposed system for Deep learning method in convolution Neural Network (CNN) the Tensor Flow tool package to detect and number teeth in dental periapical films.The work burden of a dentist and the occurrences of misdiagnosis may be reduced if intelligent dental Xray film interpretation tools are developed to improve the quality of dental care. From this perspective , automatic teeth identification using digitized films is an important task for smart healthcare.To achieve high-accuracy segmentation and classification in dental Image  to developed image-processing algorithms.

Keywords – R-CNN, Deep learning, Tensor Flow.

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