TY - GEN
T1 - Underwater moving target detection based on image enhancement
AU - Zhou, Yan
AU - Li, Qingwu
AU - Huo, Guanying
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - Motion detection in underwater video scenes is very important for many underwater computer vision tasks, such as target location, recognition and tracking. However, due to the strong optical attenuation and light scattering in water, underwater images are essentially characterized by their poor visibility, especially the low contrast and distorted information. To solve these situations, underwater moving target detection algorithm based on image enhancement is presented. The algorithm improves the contrast and clarity of the target by an adaptive underwater color image enhancement, and then extracts the moving targets by using ViBe background model. Experimental results show that the proposed algorithm can effectively extract the complete moving target by overcoming the impact of underwater environment.
AB - Motion detection in underwater video scenes is very important for many underwater computer vision tasks, such as target location, recognition and tracking. However, due to the strong optical attenuation and light scattering in water, underwater images are essentially characterized by their poor visibility, especially the low contrast and distorted information. To solve these situations, underwater moving target detection algorithm based on image enhancement is presented. The algorithm improves the contrast and clarity of the target by an adaptive underwater color image enhancement, and then extracts the moving targets by using ViBe background model. Experimental results show that the proposed algorithm can effectively extract the complete moving target by overcoming the impact of underwater environment.
KW - Adaptive image enhancement
KW - Background subtraction
KW - Underwater moving target detection
KW - ViBe model
UR - https://www.scopus.com/pages/publications/85021774065
U2 - 10.1007/978-3-319-59081-3_50
DO - 10.1007/978-3-319-59081-3_50
M3 - 会议稿件
AN - SCOPUS:85021774065
SN - 9783319590806
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 427
EP - 436
BT - Advances in Neural Networks - ISNN 2017 - 14th International Symposium, ISNN 2017, Proceedings
A2 - Cong, Fengyu
A2 - Wei, Qinglai
A2 - Leung, Andrew
PB - Springer Verlag
T2 - 14th International Symposium on Neural Networks, ISNN 2017
Y2 - 21 June 2017 through 26 June 2017
ER -