Paper Contents
Abstract
This paper presents a concise review of recent advancements in signboard translation systems, focusing on text detection, recognition, and translation techniques. It highlights key contributions such as robust traffic sign recognition in complex environments, neural network and machine learning approaches, and mobile-friendly solutions for real-time translation. The review also explores cultural and linguistic challenges in translation and emerging scene-text to scene-text translation models. Overall, it provides insights into the evolving landscape of multilingual signboard translators and outlines directions for future research in this field. By synthesizing findings from these diverse studies, this paper aims to offer valuable insights into the current landscape, challenges, and future research directions in the domain of signboard translation systems. The survey underscores the growing need for multilingual, real-time, and context-sensitive solutions that ensure accessibility and inclusivity for users across different regions and language backgrounds.
Copyright
Copyright © 2025 Raparthi Bhoomika. This is an open access article distributed under the Creative Commons Attribution License.
