Census transform-based static caption detection for frame rate up-conversion
Gyujin Bae, Young Hwan Kim, Suk‐Ju Kang · 2017
This paper presents a new static caption detection method that uses the census transform (CT) and motion vector (MV) for frame rate up-conversion. The proposed method splits a frame into several blocks and detects the static regions using CT and MV. CT is used to consider the spatio-temporal consistency of the texture and MV is used to remove the non-static regions containing moving objects. Next, it corrects the falsely detected regions by performing the outlier removal and inward filling. Finally, it detects the static caption based on the existence of global motion. In the experimental results, the average F1 score of the proposed method was up to 0.704 higher than those of the benchmark methods.