Comparison between image forgery detection algorithms

Today, the manipulation on the digital images has become a very easy and professional process using the capabilities of photo editing tools with the wide and rapid development in information technology and computer industry. Image forgery can be used to hide or manipulate important information of official documents, which can be considered as a digital crime. Many algorithms can be used to detect forged images. This paper introduces a theatrical comparison between four of the recent forgery detection algorithms; SVM, DCT, Expanding Block-based algorithm and Generic Algorithm with the aim to come up with the most efficient algorithm among the four algorithms. This was achieved by reviewing literatures of recent and relevant works whereas we focused on the accuracy. The comparison shows that GA is the most effective algorithm for detecting the image forgery, which gives the highest accuracy while DCT

Sturdy MASH D-S modulator

AnewD-S modulator is proposed. Its operation is similar to that of a multi-stage noise-shaping structure but requires no digital noise cancellation filters. Thus, the need for matching required between analogue and digital filters is eliminated. Simulation results and mathematical analysis demonstrate the effectiveness of this structure. Introduction: With delta-sigma (D-S) modulators (DSMs) heading towards low-power high-speed applications with low oversampling ratio (OSR), the employing of higher-order noise shaping is necessary to achieve the desired signal-to-noise-and-distortion ratio (SNDR). The single-loop high-order DSM can provide the required SNDR wit