• Dr P Sreenivasulu
• B Prakash
• C Mega Syam
• B Madhu sudhan

Images and videos have evolved into the primary data transporters in the modern era. The simplest video in TV news is frequently acknowledged as a confirmation of the accuracy of the reported news. Similarly, video observation and recordings can be used as primary trial material in a formal courtroom. Along with undeniable benefits, the availability of advanced visual media has a significant disadvantage. Image processing experts can undoubtedly access and alter image content in such a way that its significance is preserved. Outwardly noticeable follows are lost. Furthermore, with the ease of access to editing tools, the craft of modifying, and Forging visual substance is no longer confined to specialists. As a result, image manipulation for malicious purposes has increased. Digital forensics is the process of discovering and translating electronic data. The procedure's goal is to detect any proof in its most basic structure whereas conducting an organized examination by gathering, distinguishing, and approving computerized data for the purpose of procreating past affirmation. Forgery detection methodologies are typically classified into two types: active forensics and passive forensics, with digital watermarking and digital signatures being examples of active techniques. In contrast to these approaches, passive image forensics techniques work in the absence of a watermark or signature. These methods are based on the idea that, while digital forgeries may leave no visible signs of tampering, they may alter the underlying statistics of an image. The set of image forensic tools can be divided into five categories: 1) pixel-based methodologies for detecting statistical anomalies introduced at the pixel level, 2) format-based techniques that take advantage of statistical correlations introduced by a specific lossy compression scheme,3) camera-based methods that take advantage of artifacts introduced by the camera lens, sensor, or on-chip post processing, 4) physically-based techniques that explicitly model and detect anomalies in the three-dimensional interaction of physical objects, light, and the camera, and 5) geometric-based techniques that make measurements of objects in the world and their positions relative to the camera.

Image tampering detection, Image tampering localization, journal, Image forgery detection, Image forensics.

"PAN CARD TAMPERING IDENTIFICATION SYSTEM USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.e13-e23, May-2024, Available :http://www.jetir.org/papers/JETIR2405403.pdf

"PAN CARD TAMPERING IDENTIFICATION SYSTEM USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppe13-e23, May-2024, Available at : http://www.jetir.org/papers/JETIR2405403.pdf