IMAGE-BASED PROCESSING SYSTEM FOR ENHANCING DIGITAL IMAGE AUTHENTICATION
Abstract
In situations where picture manipulation and fraud are common, digital image authentication plays a critical role in guaranteeing the integrity and validity of digital images. An image-based processing method intended to improve digital picture authentication is presented in this study. The system uses sophisticated image processing methods to identify and evaluate different kinds of image modifications, such as edge detection, noise patterns, unnatural colors. By utilizing machine learning algorithms, the technology helps with authentication by automatically detecting suspicious areas and artifacts that point to image modification. The efficacy and dependability of the suggested approach in identifying and authenticating digital images against different types of manipulation and counterfeiting are demonstrated through experimental assessments. All things considered, the image-based processing system provides a useful instrument for supporting digital image authentication initiatives, protecting the reliability and validity of digital imagery in a variety of applications.
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