DOI QR코드

DOI QR Code

Design of Line Scratch Detection and Restoration Algorithm using GPU

GPU를 이용한 선형 스크래치 탐지와 복원 알고리즘의 설계

  • Received : 2013.11.15
  • Accepted : 2014.02.28
  • Published : 2014.04.30

Abstract

This paper proposes a linear scratch detection and restoration algorithm using pixel data comparison in a single frame or consecutive frames. There exists a high parallelism in that a scratch detection and restoration algorithm needs a large amount of comparison operations. The proposed scratch detection and restoration algorithm is designed with a GPU for fast computation. We test the proposed algorithm in sequential and parallel processing with the set of digital videos in National Archive of Korea. In the experiments, the scratch detection rate of consecutive frames is as fast as about 20% for that of a single frame. The detection and restoration rates of a GPU-based algorithm are similar to those of a CPU-based algorithm, but the parallel implementation speeds up to about 50 times.

본 논문은 화소 데이터의 비교를 이용한 단일 프레임 또는 연속 프레임에 나타나는 선형 스크래치를 탐지하여 복원하는 알고리즘을 제안하였다. 스크래치탐지와 복원방법은 프레임 간 많은 비교 연산시간을 필요로 하며 병렬처리 가능성이 높다. 제안하는 스크래치 탐지와 복원방법은 빠른 처리를 위해 GPU에서 수행할 수 있도록 병렬 설계 하였다. 제안하는 알고리즘은 국가 기록원 디지털화 영상에 대해 순차처리와 병렬처리의 성능 테스트를 수행하였다. 실험에서 연속한 스크래치를 고려하는 경우의 탐지율은 단일 프레임만 고려하는 방법보다 20% 이상 성능이 향상되었다. GPU 기반 알고리즘의 탐지율과 복원율은 CPU 기반의 알고리즘과 유사하였으나 50배 이상의 연산속도가 향상되었다.

Keywords

References

  1. D. Vitulano, V. Bruni, P. Ciarlini, "Line Scratch Detection on Digital Image: An Energy Based Model," WSCG'2002 10th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2002, pp. 447-484, Pilsen, Czech, Feb. 2002.
  2. Y. Ma, K. Xie, M. Peng, "A Parallel Gaussian Filtering Algorithm Based on Color Difference," IPTC, 2011 2nd International Symposium, pp. 51-54, Hubei, China, Oct. 2011.
  3. K. T. Kim, E. C. Ko, E. Y. Kim, "Digital Film Line Scratch Restoration based on Spatial Information," Korea Computer Congress, vol. 34, no. 1, pp. 454-459, June 2007.
  4. A. C. Kokaram, "Detection and Removal of Line Scratches in Degraded Motion Picture Sequences," in Proc. Signal Processing VIII : Theories and Application, pp. 5-8, Trieste, Italy, Sept. 1996.
  5. V. Bruni, D. Vitulano, "A Generalized Model for Scratch Detection," Image Processing, IEEE Transaction on, vol. 13, no. 1, pp. 44-50, Jan. 2004. https://doi.org/10.1109/TIP.2003.817231
  6. M. K. Gullu, O. Urhan, S. Erturk, "Scratch Detection via Temporal Coherency Analysis and Removal using Edge Priority Based Interpolation," in Proc. IEEE Intl. Symposium on Circuits and Systems, pp. 92-96, Island of Kos, Greece, May 2006.
  7. B. M. You, K. T. Jung, S. K. Kim, D. S. Hwang, "Detection and Restoration of Vertical Non-linear Scratches in Digitized Film Sequence", in the 2012 Intl. Conf. on Image Processing, Computer Vision, and Pattern Recognition, Las Vegas, NV, July 2012.
  8. NVIDIA, CUDA C Best Practices Guide, [online] Available: http://docs.nvidia.com/cuda/cuda-cbest-practices-guide/index.html.
  9. David B. Kirk, Wenmei W. Hwu, Programming Massively Parallel Processors:A Hands-on Approach, Elsevier, pp. 99-103, 2010.
  10. Jason Sanders, Edward Kandrot, CUDA By Example An Introduction to General-Purpose GPU Programming, Addison Wesley, pp. 79-81, 2010.
  11. Marie Vans, Sagi Schein, Carl Staelin, Pavel Kisilev, Steven Simske, Ram Dagan, Shlomo Harush, "Automatic Visual Inspection and Defect Detection on Variable Data Prints," Journal of Electronic Imaging, vol. 20, no. 1, pp. Feb. 2011.
  12. NVIDIA, NVIDIA Manufacturing Day 2013, [online]Available: https://registration.gputechconf.com/form/session-listing.
  13. Rob Farber, CUDA Applicatioin Design and Development, Elsevier, pp. 111-115, 2011.