Spatiotemporal directional coherence-based scrolling-text detection for frame rate up-conversion |
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| Affiliation: | 1. School of Electronic Engineering, Kumoh National Institute of Technology, Gumi, Gyeongbuk 39177, Republic of Korea;2. The division of AI Software Convergence, Dongguk University, Seoul 04620, Republic of Korea;1. State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China;2. School of Computer Science and Engineering, Beihang University, Beijing 100191, China;3. Schoolof Computer Scienceand Technology,Civil Aviation University of China, Tianjin 300300, China;1. College of Faculty of Printing, Packaging Engineering and Digital Media Technology, Xi’an University of Technology, Xi’an 710048, China;2. Key Lab of Printing and Packaging Engineering of Shaanxi Province, Xi’an 710048, China;3. Printing and Packaging Engineering Technology Research Centre of Shaanxi Province, Xi’an 710048, China;1. College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China;2. State Key Laboratory of Luminescent Materials and Devices, South China University of Technology, Guangzhou 510641, China;1. Department of Biochemistry and Biophysics, School of Basic Medical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China;2. School of Basic Medical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China;3. School of Basic Medical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China;4. School of Basic Medical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China;5. Division of Cervical Spine, Department of Orthopaedic, Third Hospital of Peking University, 49 Huayuanbei Road, Beijing 100191, China;6. Division of Cervical Spine, Department of Orthopaedic, Third Hospital of Peking University, 49 Huayuanbei Road, Beijing 100191, China;7. Division of Cervical Spine, Department of Orthopaedic, Third Hospital of Peking University, 49 Huayuanbei Road, Beijing 100191, China;8. Neuroscience Research Institute and Key Laboratory for Neuroscience, Ministry of Education/National Health Commission of China, Peking University, 38 Xueyuan Road, Beijing 100191, China |
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| Abstract: | This paper proposes a novel scrolling-text detection method that uses spatiotemporal directional coherence for frame rate up-conversion. Spatiotemporal directional coherence is defined as the coherence level of the spatiotemporal gradient distribution in consecutive frames. Existing scrolling-text detection methods usually detect text using the motion vectors of an image or the distributions of gradient components. The number of motion vectors to determine the scrolling-text decreases at the start and end points of the frame boundary. Therefore, they have difficulty accurately detecting the scrolling text from the start or end points of a frame boundary. The distributions of gradient components can be generated by non-scrolling-text components and they cannot consider the temporal information of consecutive frames, so they may erroneously detect non-scrolling-text regions as the scrolling-text. Unlike the previous methods, which are vulnerable to the presence of texture and noise, the core idea of the proposed method is to use the spatiotemporal directional coherence of the gradient components in the consecutive frames to detect the regions with a dominant edge orientation component for generation of the scrolling-text map and use bit codes from the luminance values to analyze the diversity of luminance patterns for refinement process. With these, the proposed method can further improve the detection accuracy compared to the benchmark methods. The experimental results showed that the proposed method enhanced the average F1 score by up to 0.5195 (a 137.69 % improvement) compared to the benchmark methods. The average computation time per pixel of the proposed method was also reduced by up to 16.205 μs (a 70.57 % reduction) compared to the benchmark methods. |
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| Keywords: | Frame rate up-conversion Scrolling-text detection Spatiotemporal directional coherence Motion estimation |
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