Digital images have been used in emerging applications, where their authenticity is quite importance. This proves to be problematic due to the widespread availability of digital image editing software. As a result, there is a great need for the development of reliable techniques for verifying the integrity of digital images. In this paper, we propose a novel technique based on blind forensic method to attest the image authenticity. This paper presents the efficient method of digital blind forensics within the medical imaging field with the objective to detect whether an image has been modified by some processing. It compares two image features: the histogram statistics of reorganized block-based discrete cosine transform coefficients, originally proposed for steganalysis purposes, and the histogram statistics of reorganized block-based Tchebichef moments. Both features serve as input of a set of support vector machine classifiers built in order to discriminate tampered images from original ones as well as to identify the nature of the global modification.