Skyline Extraction using a Multistage Edge Filtering
Skyline extraction in mountainous images can be used
for navigation of vehicles or UAV(unmanned air vehicles), but it is
very hard to extract skyline shape because of clutters like clouds, sea
lines and field borders in images. We developed the edge-based
skyline extraction algorithm using a proposed multistage edge filtering
(MEF) technique. In this method, characteristics of clutters in the
image are first defined and then the lines classified as clutters are
eliminated by stages using the proposed MEF technique. After this
processing, we select the last line using skyline measures among the
remained lines. This proposed algorithm is robust under severe
environments with clutters and has even good performance for
infrared sensor images with a low resolution. We tested this proposed
algorithm for images obtained in the field by an infrared camera and
confirmed that the proposed algorithm produced a better performance
and faster processing time than conventional algorithms.
[1] Raj Talluri and J, K, Aggarwal, "Position estimation for an autonomous
mobile robot in an outdoor environment," IEEE Trans. Robotics and
automation, vol. 8, no. 5, pp. 573 ~ 584, 1992.
[2] Scott M. Ettinger, et. al., "Vision-guide flight stability and control for
micro air vehicles," Proc. IEEE/RSJ Int-l Conf. Intelligent Robots and
System (IROS-02), pp. 2134 ~ 2140, 1993.
[3] Fang, M., Chiu, M.-Y., Liang, C.-C., Singh, "A skyline for video-based
virtual rail for vehicle navigation,", Proc. IEEE Int. Sympos. On
Intelligent Vehicles, pp. 207 ~ 212, 1993.
[4] Wen-Nung Lie, Tom C.-I. Lin, Ting-Chih Lin, Keng-Shen Hung, "A
robust dynamic programming algorithm to extract skyline in images for
navigation," Pattern Recognition Letters, vol. 26, pp. 221 ~ 230, 2005.
[5] Ji Hwan Woo and In So Kwen, "Robust horizon and peak extraction for
vision-based navigation," IAPR workshop on Machine Vision
Applications, 2005.
[6] Sung Woo Yang, Ihn Cheol Kim and Jin Soo Kim, "Robust skyline
extraction algorithm for mountainous images," VISAPP (International
Conference on Computer Vision Theory and Applications), 2007.
[7] Canny, J., "A computational theory for edge detection," IEEE Trans. On
Pattern Recognition and Machine Intelligence, vol. 26, no. 6, pp. 679 ~
698, 1986.
[8] Forsyth, D. A. and Ponce, J., "Computer vision a modern approach,"
Prentice Hall, Upper Saddle River, NJ, 2003.
[1] Raj Talluri and J, K, Aggarwal, "Position estimation for an autonomous
mobile robot in an outdoor environment," IEEE Trans. Robotics and
automation, vol. 8, no. 5, pp. 573 ~ 584, 1992.
[2] Scott M. Ettinger, et. al., "Vision-guide flight stability and control for
micro air vehicles," Proc. IEEE/RSJ Int-l Conf. Intelligent Robots and
System (IROS-02), pp. 2134 ~ 2140, 1993.
[3] Fang, M., Chiu, M.-Y., Liang, C.-C., Singh, "A skyline for video-based
virtual rail for vehicle navigation,", Proc. IEEE Int. Sympos. On
Intelligent Vehicles, pp. 207 ~ 212, 1993.
[4] Wen-Nung Lie, Tom C.-I. Lin, Ting-Chih Lin, Keng-Shen Hung, "A
robust dynamic programming algorithm to extract skyline in images for
navigation," Pattern Recognition Letters, vol. 26, pp. 221 ~ 230, 2005.
[5] Ji Hwan Woo and In So Kwen, "Robust horizon and peak extraction for
vision-based navigation," IAPR workshop on Machine Vision
Applications, 2005.
[6] Sung Woo Yang, Ihn Cheol Kim and Jin Soo Kim, "Robust skyline
extraction algorithm for mountainous images," VISAPP (International
Conference on Computer Vision Theory and Applications), 2007.
[7] Canny, J., "A computational theory for edge detection," IEEE Trans. On
Pattern Recognition and Machine Intelligence, vol. 26, no. 6, pp. 679 ~
698, 1986.
[8] Forsyth, D. A. and Ponce, J., "Computer vision a modern approach,"
Prentice Hall, Upper Saddle River, NJ, 2003.
@article{"International Journal of Electrical, Electronic and Communication Sciences:59495", author = "Byung-Ju Kim and Jong-Jin Shin and Hwa-Jin Nam and Jin-Soo Kim", title = "Skyline Extraction using a Multistage Edge Filtering", abstract = "Skyline extraction in mountainous images can be used
for navigation of vehicles or UAV(unmanned air vehicles), but it is
very hard to extract skyline shape because of clutters like clouds, sea
lines and field borders in images. We developed the edge-based
skyline extraction algorithm using a proposed multistage edge filtering
(MEF) technique. In this method, characteristics of clutters in the
image are first defined and then the lines classified as clutters are
eliminated by stages using the proposed MEF technique. After this
processing, we select the last line using skyline measures among the
remained lines. This proposed algorithm is robust under severe
environments with clutters and has even good performance for
infrared sensor images with a low resolution. We tested this proposed
algorithm for images obtained in the field by an infrared camera and
confirmed that the proposed algorithm produced a better performance
and faster processing time than conventional algorithms.", keywords = "MEF, mountainous image, navigation, skyline", volume = "5", number = "7", pages = "860-5", }