Human Dental Age and Gender Assessment from Dental Radiographs Using Deep Convolutional Neural Network


  • B. Hemalatha Department of Information Technology, Dr. N. G. P. Institute of Technology, Coimbatore 641 035, India.
  • P. Bhuvaneswari Department of Computer Science and Engineering, Sona College of Technology, Salem,636005, Tamilnadu, India.
  • Mahesh Nataraj Department of Electronics and Instrumentation Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India.
  • G. Shanmugavadivel Department of Electronics and Communication Engineering, M.Kumarasamy College of Engineering, Karur-639113, Tamilnadu, India.



Chronological age, gender, deep learning, classification, optimization, segmentation, DCNN


Human gender and age identification play a prominent role in forensics, bio-archaeology, and anthropology. Dental images provide prominent indications used for the treatment or diagnosis of disease and forensic investigation. Numerous dental age identification techniques come with specific boundaries, namely minimum reliability and accuracy. Gender identification approaches are not widely researched, whereas the effectiveness and accuracy of classification are not practical and very minimal. Drawbacks in the existing system are considered in the formulation of the proposed approach. Deep learning approaches can effectively rectify issues of drawbacks in other classifiers. The accuracy and performance of a classifier are enhanced with the deep convolutional neural network. The fuzzy C-Means Clustering approach is used for segmentation, and Ant Lion Optimization is used for optimal feature score selection. The selected features are classified using a deep convolutional neural network (DCNN). The performance of the proposed technique is investigated with existing classifiers, and DCNN outperforms other classifiers. The proposed technique achieves 91.7% and 91% accuracy for the identification of gender and age, respectively.

Author Biography

B. Hemalatha, Department of Information Technology, Dr. N. G. P. Institute of Technology, Coimbatore 641 035, India.