Digital dental models are widely used compared to dental impressions or plaster-dental models for occlusal analysis as well as fabrication of prosthodontic and orthodontic appliances. The digital dental model has been considered as one of the significant measures for the analysis of dental occlusion. However, the process requires more computation time with less accuracy during the re-establishment of dental occlusion. In this research, a modern method to re-establish dental occlusion has been designed using a Reconstructed-based Identical Matrix Point (RIMP) technique. The curvature of the dental regions has been reconstructed using distance mapping in order to minimize the computation time, and an iterative point matching approach is used for accurate re-establishment. Satisfactory restoration and occlusion tests have been analyzed using a dental experimental setup with high-quality digital camera images. Further, the high-quality camera images are converted to grayscale images for mathematical computation using MATLAB image processing toolbox. Besides, 70 images have been taken into consideration in which 30 planar view images has been utilized for experimental analysis. Indeed, based on the outcomes, the proposed RIMP outperforms overall accuracy of (91.50%) and efficiency of (87.50%) in comparison with conventional methods such as GLCM, PCR, Fuzzy C Means, OPOS, and OGS.