Image Retrieval Based on LBP Pyramidal Multiresolution using Reversible Watermarking
This work addresses privacy and retrieval efficiency in medical image databases for clinical applications, but it appears incremental as it combines existing techniques like LBP and reversible watermarking.
The paper tackles the problem of retrieving medical images from databases by developing a descriptor based on Local Binary Pattern (LBP) pyramidal multiresolution analysis for texture, and embeds this descriptor along with patient information into images using reversible watermarking to ensure privacy, resulting in a unified entity that prevents unauthorized access to patient data.
In the medical field, images are increasingly used to facilitate diagnosis of diseases. These images are stored in multimedia databases accompanied by doctor s prescriptions and other information related to patients.Search for medical images has become for clinical applications an essential tool to bring effective aid in diagnosis. Content Based Image Retrieval (CBIR) is one of the possible solutions to effectively manage these databases. Our contribution is to define a relevant descriptor to retrieve images based on multiresolution analysis of texture using Local Binary Pattern LBP. This descriptor once calculated and information s relating to the patient; will be placed in the image using the technique of reversible watermarking. Thereby, the image, descriptor of its contents, the BFILE locator and patientrelated information become a single entity, so even the administrator cannot have access to the patient private data.