Image Retrieval Based on LBP Pyramidal Multiresolution using Reversible Watermarking

TL;DR

This paper proposes a content-based medical image retrieval method using a multiresolution Local Binary Pattern descriptor, embedded via reversible watermarking to protect patient privacy while integrating image and metadata.

Contribution

It introduces a novel descriptor for texture analysis in medical images and combines it with reversible watermarking to secure patient data within the image.

Findings

Effective retrieval of medical images based on texture features.

Secure embedding of image and patient information into a single entity.

Enhanced privacy protection in medical image databases.

Abstract

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.