Gradient Magnitude Differences and Guided Filter for Stereo Video Matching Algorithm
Keywords:
Computer Vision, Gradient Matching, Guided Filter, Stereo Matching Algorithm,Abstract
This paper proposes a new stereo video matching algorithm which uses Gradient Magnitude (GM) differences and Guided Filter (GF). The radiometric and edges distortions are the problems that contribute to the quality of the results for stereo video matching algorithm. Hence, this article proposes an algorithm to reduce these problems. The first stage, the GM is utilized. The GM is strong against the radiometric distortion on an image due to different brightness on an image or between the stereo cameras. The second stage, the GF is used to improve the edges of object matching and is efficiently to remove the noise. Based on the standard benchmarking stereo dataset, the proposed work in this article produces good results and performs much better compared to before the proposed framework. This new algorithm is also competitive with some established methods in the literature.References
R. A. Hamzah, H. Ibrahim, and A. H. A. Hassan, “Stereo matching algorithm for 3d surface reconstruction based on triangulation principle,” in International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE), IEEE, 2016, pp. 119–124.
D. Scharstein, R. Szeliski, and R. Zabih, “A taxonomy and evaluation of dense two-frame stereo correspondence algorithms,” in IEEE Workshop on Stereo and Multi-Baseline Vision, 2001.(SMBV 2001). IEEE, 2001, pp. 131–140.
R. A. Hamzah and H. Ibrahim, “Literature survey on stereo vision disparity map algorithms,” Journal of Sensors, vol. 2016, pp. 1-23, 2016.
Q. Liang, Y. Yang, and B. Liu, “Stereo matching algorithm based on ground control points using graph cut,” in 2014 7th International Congress on Image and Signal Processing (CISP),. IEEE, 2014, pp. 503–508.
S.S. Wu, C.-H. Tsai, and L.G. Chen, “Efficient hardware architecture for large disparity range stereo matching based on belief propagation,” in 2016 IEEE International Workshop on Signal Processing Systems (SiPS), IEEE, 2016, pp. 236–241.
R. A. Hamzah, K.A.A. Aziz, and A.S.M. Shokri, “A pixel to pixel correspondence and region of interest in stereo vision application,” In IEEE Symposium on Computers & Informatics (ISCI), 2012, pp. 193- 197.
J. Zbontar and Y. LeCun, “Computing the stereo matching cost with a convolutional neural network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 1592–1599.
W. Hu, K. Zhang, L. Sun, J. Li, Y. Li, and S. Yang, “Virtual support window for adaptive-weight stereo matching,” in 2011 IEEE Visual Communications and Image Processing (VCIP), 2011, pp. 1–4.
N. Einecke and J. Eggert, “Anisotropic median filtering for stereo disparity map refinement.” in VISAPP (2), 2013, pp. 189–198.
K. He, J. Sun, and X. Tang, “Guided image filtering,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 6, pp. 1397–1409, 2013.
R. A. Hamzah, H. Ibrahim, and A. H. A. Hassan, “Stereo matching algorithm based on per pixel difference adjustment, iterative guided filter and graph segmentation,” Journal of Visual Communication and Image Representation, vol. 42, pp. 145–160, 2017.
M. Menze and A. Geiger, “Object scene flow for autonomous vehicles,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 3061–3070.
R.A. Hamzah, A.F. Kadmin, S.F.A. Ghani, M.S. Hamid, and S. Salam, “Disparity refinement process based on RANSAC plane fitting for machine vision applications,” Journal of Fundamental and Applied Sciences, 9(4S), pp. 226-237, 2017.
R. A. Hamzah, M. S. Hamid, H. N. Rosly, and N. M. Z. Hashim, “An Aligned epipolar line for stereo images with multiple sizes ROI in depth maps for computer vision application,” International Journal of Information and Education Technology, 1(1), pp. 15-19, 2011.
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