Enhancement of the Detection for Intelligent Vehicle Systems - Case Rain/Snow
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Intelligent vehicle systems based on vision clearly have remarkably progressed. However, they still suffer from the degradation of results quality in case of unfavorable acquisition conditions as fog, rain, and snow. Few works, where the aim is to enhance the visibility and reduce the effect of weather conditions like rain and snow, can be quoted in the context of intelligent vehicle systems. In this work, the authors established a method to enhance vehicles detection, in case of rain/snow. This method gathers a succession of phases: the extraction of the characteristics of Gaussian susceptible fields -type Gaussian -, the separation of these characteristics in two objects classes according to the criteria of the area, the modeling of the small area in a form of ellipses where one of those parameters ‘orientation’ was exploited, the distinction between the small objects that represent rain / snow and those that represent the rest of details of big objects based on probability laws, the elimination of small objects representing rain/snow and the exploitation of the big objects for the detection of vehicles. This detection enhancement method allowed a considerable increase in the detection rate.
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Abbas, M., Karsiti, M., Napiah, M., Brahim, S., Integrated Self-Organized Traffic Light Controllers for Signalized Intersections, (2013) International Review of Automatic Control (IREACO), 6 (4), pp. 481-488.
Asaidi, H., Aarab, A., Bellouki, M., Adaptive Background Modeling Algorithm Based on Objects Dynamicity, (2013) International Review on Computers and Software (IRECOS), 8 (9), pp. 2036-2043.
Lucia Janušová, Silvia Cicmancová, Improving Safety of Transportation by Using Intelligent Transport Systems, Procedia Engineering, Volume 134, 2016, Pages 14-22, ISSN 1877-7058.
Santhaseelan V., Asari V.K. (2011) Phase Congruency Based Technique for the Removal of Rain from Video. In: Kamel M., Campilho A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6753.
M. Desvignes and G. Molinié, "Raindrops size and shape from videosonde and image processing," 2012 IEEE International Symposium on Industrial Electronics, Hangzhou, 2012, pp. 1164-1167.
Qui Wu and all, “ Raindrop detection and removal using salient visual features”, Image Processing (ICIP), 2012 19th IEEE International Conference on.
Jérime Bousou,Nicolas Hautière and Jean Philippe Tarel "Rain or Snow Detection in Image Sequences through use of a Histogram of orientation of Streaks", International journal of Computer Vision, 2011.
Kshitiz Gang and Shree K Nayar, “When does camera see rain?”, in Proc. IEEE Int. Conf. Comput. Vis., vol. . Oct. 2005, pp. 1067-1074..
Peter Barnum, and all, “Spatio-temporal frequency analysis for removing rain and snow from video”, 2007.
M. Zhou, Z. Zhu, R. Deng and S. Fang, "Rain detection and removal of sequential images," 2011 Chinese Control and Decision Conference (CCDC), Mianyang, 2011, pp. 615-618.
X. Xue, X. Jin, C. Zhang and S. Goto, "Motion robust rain detection and removal from videos," 2012 IEEE 14th International Workshop on Multimedia Signal Processing (MMSP), Banff, AB, 2012, pp. 170-174.
A. Cord and D. Aubert, "Towards rain detection through use of in-vehicle multipurpose cameras," 2011 IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, 2011, pp. 833-838.
Minmin Shen, and Ping Xue, “A fast algorithm for rain detection and removal from video”, Proceeding, ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo, Pages 1-6.
H. Sakaino, Yang Shen, Yuanhang Pang and Lizhuang Ma, "Falling snow motion estimation based on a semi-transparent and particle trajectory model," 2009 16th IEEE International Conference on Image Processing (ICIP), Cairo, 2009, pp. 1609-1612.
John Ruiz-Hernandez, James L. Crowley, "Facial analysis with Gaussian Derivative”, Thesis of Grenoble University, 2011.
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