Motion Analysis for Duplicate Frame Removal in Wireless Capsule Endoscope Video
Wireless capsule Endoscopy (WCE) has rapidly
shown its wide applications in medical domain last ten years
thanks to its noninvasiveness for patients and support for thorough
inspection through a patient-s entire digestive system including
small intestine. However, one of the main barriers to efficient
clinical inspection procedure is that it requires large amount of
effort for clinicians to inspect huge data collected during the
examination, i.e., over 55,000 frames in video. In this paper, we
propose a method to compute meaningful motion changes of
WCE by analyzing the obtained video frames based on regional
optical flow estimations. The computed motion vectors are used to
remove duplicate video frames caused by WCE-s imaging nature,
such as repetitive forward-backward motions from peristaltic
movements. The motion vectors are derived by calculating
directional component vectors in four local regions. Our
experiments are performed on small intestine area, which is of
main interest to clinical experts when using WCEs, and our
experimental results show significant frame reductions comparing
with a simple frame-to-frame similarity-based image reduction
method.
[1] G. Iddan, G. Meron, A. Glukhovsky, P. Swain,
"Wireless capsule endoscopy", Nature, vol. 405, Issue 6785,
pp. 417-418, 2000.
[2] S. Hwang, J. H. Oh, J. Cox, S. J. Tang, H. F. Tibbals,
"Blood detection in wireless capsule endoscopy using
expectation maximization clustering", Proceedings of SPIE,
vol. 6144, pp. 577-587, 2006.
[3] J. Berens, M. Mackiewicz, D. Bell, "Stomach, intestine
and colon tissue discriminators for wireless capsule
endoscopy images", Proceedings of SPIE, Conference on
Medical Imaging, vol. 5747, pp. 283-290, 2005.
[4] B. Li, MQH. Meng, "Texture analysis for ulcer
detection in capsule endoscopy images", Image and Vision
Computing, vol. 27, pp. 1336-1342, 2009.
[5] B. Li, MQH. Meng, "Computer-based detection of
bleeding and ulcer in wireless capsule endoscopy images
by chromaticity moments", Computer in Biology and
Medicine, pp. 141-147, 2009.
[6] Berthold K. P. Horn, Brian G. Schunck, "Determining
Optical Flow", Artificial Intelligence, pp. 185-203, 1981.
[7] P. Anandan, "A computational framework and an
algorithm for the measurement of visual motion",
International Journal of Computer Vision, 2, pp. 283-310,
1989.
[8] E. Memin, P. Perez, "Hierarchical estimation and
segmentation of dense motion fields", International
Journal of Computer Vision, 46(2), pp. 129-155, 2002.
[9] T. Brox, A. Bruhn, N. Papenberg, J. Weickert, "High
accuracy optical flow estimation based on a theory for
warping", European Conference on Computer Vision,
LNCS 3024, pp. 25-36, 2004.
[10] S. Uras, F. Girosi, A. Verri, and V. Torre. "A
computational approach to motion perception", Biological
Cybernetics, 60, pp. 79-87, 1988.
[11] M. J.Black. P. Anandan, "The robust estimation of
multiple motions: parametric and piecewise smooth flow
fields", Computer Vision and Image Understanding, 63(1),
pp. 75-104, 1996.
[12] E. Memin. P. Perez, "A multigrid approach for
hierarchical motion estimation", In Proc. Sixth
International Conference on Computer Vision, pp. 933-938,
1998
[13] L. I. Rudin, S. Osher, E. Fatemi, "Nonlinear total
variation based noise removal algorithms", Physica D, 60,
pp. 259-268, 1992.
[14] I. Cohen, "Nonlinear variational method for optical
flow computation", Proc. Eighth Scan-dinavian Conference
on Image Analysis, volume 1, pp. 523-530, 1993
[15] L. Alvarez, J. Esclarin, M. Lefebure, J. Sanchez, "A
PDE model for computing the optical flow", In Proc. XVI
Congreso de Ecuaciones Diferenciales y Aplicationes,
pp.1349-1356, 1999., 1999.
[1] G. Iddan, G. Meron, A. Glukhovsky, P. Swain,
"Wireless capsule endoscopy", Nature, vol. 405, Issue 6785,
pp. 417-418, 2000.
[2] S. Hwang, J. H. Oh, J. Cox, S. J. Tang, H. F. Tibbals,
"Blood detection in wireless capsule endoscopy using
expectation maximization clustering", Proceedings of SPIE,
vol. 6144, pp. 577-587, 2006.
[3] J. Berens, M. Mackiewicz, D. Bell, "Stomach, intestine
and colon tissue discriminators for wireless capsule
endoscopy images", Proceedings of SPIE, Conference on
Medical Imaging, vol. 5747, pp. 283-290, 2005.
[4] B. Li, MQH. Meng, "Texture analysis for ulcer
detection in capsule endoscopy images", Image and Vision
Computing, vol. 27, pp. 1336-1342, 2009.
[5] B. Li, MQH. Meng, "Computer-based detection of
bleeding and ulcer in wireless capsule endoscopy images
by chromaticity moments", Computer in Biology and
Medicine, pp. 141-147, 2009.
[6] Berthold K. P. Horn, Brian G. Schunck, "Determining
Optical Flow", Artificial Intelligence, pp. 185-203, 1981.
[7] P. Anandan, "A computational framework and an
algorithm for the measurement of visual motion",
International Journal of Computer Vision, 2, pp. 283-310,
1989.
[8] E. Memin, P. Perez, "Hierarchical estimation and
segmentation of dense motion fields", International
Journal of Computer Vision, 46(2), pp. 129-155, 2002.
[9] T. Brox, A. Bruhn, N. Papenberg, J. Weickert, "High
accuracy optical flow estimation based on a theory for
warping", European Conference on Computer Vision,
LNCS 3024, pp. 25-36, 2004.
[10] S. Uras, F. Girosi, A. Verri, and V. Torre. "A
computational approach to motion perception", Biological
Cybernetics, 60, pp. 79-87, 1988.
[11] M. J.Black. P. Anandan, "The robust estimation of
multiple motions: parametric and piecewise smooth flow
fields", Computer Vision and Image Understanding, 63(1),
pp. 75-104, 1996.
[12] E. Memin. P. Perez, "A multigrid approach for
hierarchical motion estimation", In Proc. Sixth
International Conference on Computer Vision, pp. 933-938,
1998
[13] L. I. Rudin, S. Osher, E. Fatemi, "Nonlinear total
variation based noise removal algorithms", Physica D, 60,
pp. 259-268, 1992.
[14] I. Cohen, "Nonlinear variational method for optical
flow computation", Proc. Eighth Scan-dinavian Conference
on Image Analysis, volume 1, pp. 523-530, 1993
[15] L. Alvarez, J. Esclarin, M. Lefebure, J. Sanchez, "A
PDE model for computing the optical flow", In Proc. XVI
Congreso de Ecuaciones Diferenciales y Aplicationes,
pp.1349-1356, 1999., 1999.
@article{"International Journal of Information, Control and Computer Sciences:55804", author = "Min Kook Choi and Hyun Gyu Lee and Ryan You and Byeong-Seok Shin and Sang-Chul Lee", title = "Motion Analysis for Duplicate Frame Removal in Wireless Capsule Endoscope Video", abstract = "Wireless capsule Endoscopy (WCE) has rapidly
shown its wide applications in medical domain last ten years
thanks to its noninvasiveness for patients and support for thorough
inspection through a patient-s entire digestive system including
small intestine. However, one of the main barriers to efficient
clinical inspection procedure is that it requires large amount of
effort for clinicians to inspect huge data collected during the
examination, i.e., over 55,000 frames in video. In this paper, we
propose a method to compute meaningful motion changes of
WCE by analyzing the obtained video frames based on regional
optical flow estimations. The computed motion vectors are used to
remove duplicate video frames caused by WCE-s imaging nature,
such as repetitive forward-backward motions from peristaltic
movements. The motion vectors are derived by calculating
directional component vectors in four local regions. Our
experiments are performed on small intestine area, which is of
main interest to clinical experts when using WCEs, and our
experimental results show significant frame reductions comparing
with a simple frame-to-frame similarity-based image reduction
method.", keywords = "Wireless capsule endoscopy, optical flow, duplicated image, duplicated frame.", volume = "4", number = "2", pages = "247-4", }