Real-time Video Quality Assessment for Analog Television Based on Adaptive Fuzzy Membership Function Tuning

Abstract

Real-time VQA (Video Quality Assessment) is an important part in the effort to build tracking antenna system especially for analog TV. In this case, VQA must work in real-time to assess the video clarity level. VQA assessment results are valuable information for the decision-making process. Thus, the antenna can rotate automatically looking for the ideal direction without user’s control. In addition, the video clarity level on the TV screen can reach optimum according to the user's wishes. The biggest challenge to VQA is, VQA must be able to assess the video clarity level according to the user’s visual perception. Therefore, in this study, the MOS-VQS (Mean Opinion Score-Video Quality Subjective) was used as a visual perception approach. In addition, Adaptive FIS (Fuzzy Inference System) with membership function tuning was implemented for decision making. This was conducted as an effort to build a reliable real-time VQA. The test results show that real-time VQA that has been built has a good performance. This is shown from the average accuracy percentage of the lowest assessment reached 77.2% and the highest reached 88.2%.