Dental X-ray Identification System Based on Association Rules Extracted by k-Symbol Fractional Haar Functions

Several identification approaches have recently been employed in human systems for forensic purposes to decrease efforts and boost the accuracy of identification. Dental provide automated matching by searching photographic dental features retrieve similar models. In this study, problem image was investigated developing a novel scheme (DIS) utilizing fractional wavelet feature extraction technique rule mining with an Apriori procedure. The proposed approach extracts most discriminating during process obtain strong association rules (ARs). is divided into two steps. first stage using transform based on k-symbol Haar filter (k-symbol FHF), while second algorithm AR mining, which applied find frequent patterns images. Each image’s created ARs are saved alongside database use system’s recognition. DIS method suggested study primarily enhances Apriori-based system, aims address drawbacks mining.