Medical Image Blind Integrity Verification with Krawtchouk Moments

Abstract

A new blind integrity verification method for medical image is proposed in this paper. It is based on a new kind of image features, known as Krawtchouk moments, which we use to distinguish the original images from the modified ones. Basically, with our scheme, image integrity verification is accomplished by classifying images into the original and modified categories. Experiments conducted on medical images issued from different modalities verified the validity of the proposed method and demonstrated that it can be used to detect and discriminate image modifications of different types with high accuracy. We also compared the performance of our scheme with a state-of-the-art solution suggested for medical images—solution that is based on histogram statistical properties of reorganized block-based Tchebichef moments. Conducted tests proved the better behavior of our image feature set.

Hiding data inside images using orthogonal moments

“…In order to solve this problem, discrete orthogonal moments such as Krawtchouk, Tchebichef, Hahn, Charlier and Meixner moments have been successfully introduced within the field of image analysis [27,31,50,70]. The implementation of these moments does not require any numerical approximation since the basis set is orthogonal in the discrete domain of the image coordinate space [12,44].…”