The communication between hearing impaired individuals and the general public still remains a challenge due to the lack of real time sign language interpretation systems. This paper presents a real time webcam-based sign language translation system using computer vision to facilitate efficient communication. The proposed system analyses live video feed from a standard webcam using a vision-based pipeline for hand gesture recognition. The proposed system employs hand landmarks to analyse the video feed using a strong computer vision framework, which assists in extracting precise spatial information from sign language gestures. The extracted information is then analysed and categorized to identify corresponding sign language symbols, which are then translated into readable text output in real time. The end of this research work reveals that the proposed approach is a cost effective and efficient solution for sign language translation. The solution will focus on processing, latency, and usability, making it useful for real world assistive communication problems. The experimental analysis proves the accuracy of the recognition in controlled lighting conditions and various orientations of the hand. The solution will prove that the proposed solution is cost effective and scalable for sign language translation. This research work validates the application of computer vision based assistive technology to enhance communication accessibility and inclusivity. The proposed system can be further extended to support the translation of a broader vocabulary set, dynamic signs, and multiple languages.