Most Significant Bit-Plane Based Local Ternary Pattern for Biomedical Image Retrieval

In this paper, Most Significant Bit-plane using Local Ternary Pattern is proposed for retrieval of biomedical images. Biomedical images have been evolved in hospitals and medical institutions for disease diagnosis of patients and to detect and record the patient's history. Algorithm uses transformation scheme to calculate transformed value of each neighboring pixel present in a local bit plane. The proposed method is generated by calculating two binary pattern from a ternary pattern using difference of local biplane transformed values with the intensity value of center pixel. The retrieval efficiency of proposed method is tested on two standard bio-medical databases OASIS-MRI and MESSIDOR database by using Average Retrieval Precision (ARP). We get 66.17% result on OASIS database and 56.27% on MESSIDOR dataset. The MSBPLTP is evaluated using ARP and compared with existing image retrieval methods.