TY - GEN
T1 - Segmentation based on the unstructured road with shadow
AU - Xia, Xiangxiang
AU - Zhao, Jianyu
AU - Li, Xinli
AU - Wang, Haodi
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2016/12/13
Y1 - 2016/12/13
N2 - The road detection has a very important position in automatic driving and machine vision. This paper presents a method of unstructured road images with shadow, using two-dimensional Tsallis cross entropy and Hough line detection. First we convert the RGB image to HSI (hue, saturation, intensity) space model. Then we try to find the horizontal line of the vanishing point, with calculating the normalized cross correlation (NCC) values in intensity component. Using two-dimensional Tsallis cross entropy in hue and saturation components for single threshold segmentation, we subdivide the image into road region and the background region. After that, using the logic operations to them reduces the dimension. Finally, we use the Hough line detection to detect the road edge and predict the vanishing point. The experimental results demonstrate the effectiveness of our method. © 2016 IEEE.
AB - The road detection has a very important position in automatic driving and machine vision. This paper presents a method of unstructured road images with shadow, using two-dimensional Tsallis cross entropy and Hough line detection. First we convert the RGB image to HSI (hue, saturation, intensity) space model. Then we try to find the horizontal line of the vanishing point, with calculating the normalized cross correlation (NCC) values in intensity component. Using two-dimensional Tsallis cross entropy in hue and saturation components for single threshold segmentation, we subdivide the image into road region and the background region. After that, using the logic operations to them reduces the dimension. Finally, we use the Hough line detection to detect the road edge and predict the vanishing point. The experimental results demonstrate the effectiveness of our method. © 2016 IEEE.
KW - NCC
KW - Tsallis cross entropy
KW - Unstructured road
KW - Vanishing point
UR - https://www.scopus.com/pages/publications/85010375984
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85010375984&origin=recordpage
U2 - 10.1109/IHMSC.2016.71
DO - 10.1109/IHMSC.2016.71
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781509007684
VL - 1
T3 - Proceedings - 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2016
SP - 501
EP - 504
BT - Proceedings - 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2016
PB - IEEE
T2 - 8th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2016
Y2 - 11 September 2016 through 12 September 2016
ER -