Scrolling text detection based on region characteristic analysis for frame rate up-conversion

Lee, Ho Sub; Kang, Suk‐Ju; Kim, Young Hwan

doi:10.1016/j.displa.2018.05.001

Cited by 4 publications

(15 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Histogram Scrolling-text detection is process of detecting the scrolling-text from a video to reduce the artifacts that are frequently caused by scrolling-text in FRUC. Several scrolling-text detection methods have been proposed [21]- [25]. The edge information-based scrolling-text detection method [21] detects scrolling-text depicted on the horizontal or vertical regions of the frame boundary by projecting the edge information obtained from a Sobel edge detector [12] on the horizontal or vertical axis.…”

Section: Related Workmentioning

confidence: 99%

“…Most recently, a text edge detector method [25] based on the concept of a region-adaptive threshold has been proposed. The central concept is that text edges are more likely to exist in a region with a higher luminance variation.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed method generates an initial scrolling-text map using the previous and current text maps obtained from the previous step. Before the generation of the initial scrolling-text map, because scrolling-text generally exists within the frame boundary, the result of text map detection in the frame boundary regions is considered to detect the scrolling-text, as in previous papers [21]- [25]. A temporal difference exists between the scrolling-text regions of consecutive frames.…”

Section: B Generation Of the Initial Scrolling-text Mapmentioning

confidence: 99%

“…The proposed method generates the connected components of the text edges in the result of the text edge difference map by performing a hole-filling process [25], which fills the edges on the gap between two different edges in the result of text edge difference map. In this process, the hole is the gap between two different edges in the same row on the result of the text edge difference map.…”

Section: B Generation Of the Initial Scrolling-text Mapmentioning

confidence: 99%

“…The proposed method uses this concept for the first refinement process by removing the scrolling-text region if its length is shorter than a predefined length (T3). The threshold value T3 was set to 64 empirically by observing the minimum size of scrolling-text region [25].…”

Section: Refinement Of the Scrolling-text Mapmentioning

confidence: 99%

See 4 more Smart Citations

Directional Coherence-Based Scrolling-Text Detection for Frame Rate Up-Conversion

Lee

Cho

2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

This paper proposes a new scrolling-text detection method that uses directional coherence for frame rate up-conversion (FRUC). Most previous methods use either gradient information or motion vector (MV) distribution of the frame for scrolling-text detection. Edges can be generated by non-text components and the number of MVs to determine the scrolling-text decreases in each row of the frame. Thus, they incorrectly detect the non-text regions as scrolling-text and cannot accurately detect the start or end of text scrolling at the frame boundary. The proposed method overcomes these problems using coherence values of edge directions for each pixel and scrolling-text-aware refinement processes. The key idea of the proposed method is to use the directional coherence of edge directions and use texture patterns analysis-based refinement to improve the accuracy of the scrolling-text detection. For refinement processes, the proposed method extracts texture patterns as bit codes. Then, it computes the diversity of the texture patterns around the detected text edges. In addition, the proposed method extracts the representative value of the MV for the detected region to correct the regions falsely detected as the scrolling-text. With these refinement processes, the proposed method can also accurately detect the start or end of text scrolling at the frame boundary. In the experimental results, the proposed method increased the average F1 score to 0.504 (a 131.25% improvement) compared with previous methods. The average computation time per pixel of the proposed method also decreased to 18.571 μs (an 80.80% reduction) compared with previous methods. INDEX TERMS Frame rate up-conversion, coherence of edge directions, scrolling-text detection, motion estimation.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%