Abstract
Traditional measurement methods are obtained by calculating the global disparity map. The accuracy of these methods is low and the speed is slow. Under the condition of uneven illumination, low contrast and obvious noise, they can’t meet the measurement requirements well. An underwater image enhancement method based on Contrast Limited Adaptive Histogram Equalization and image weighting fusion is proposed. For the measurement of underwater target, only two matching points are solved in the algorithm design, which improves the accuracy and speed of underwater ranging. The idea of coarse-to-fine matching is adopted, that is, the SAD algorithm is used in matching area to complete the coarse matching such that the matching windows can be determined firstly. Then the stereo matching algorithm based on NCC and Census fusion is used to decide the final matching point. The algorithm is insensitive to light and can extract edges and corners better. Finally, three-dimensional reconstruction is carried out to restore the three-dimensional coordinates of the endpoints to be measured, and the real size can be obtained by calculating the Euclidean distance between the two points. The experimental results show that the algorithm runs fast and robustly without calculating the disparity of the whole image, and the results meet the accuracy requirements.
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References
Huang, P.C., Jiang, J.Y., Yang, B.: Research status and progress of binocular stereo vision. Opt. Instrum. 39(4), 81–86 (2017)
Bai, X., Yang, Y.Z., Han, F.Y.: Research on measuring method of plane geometric dimensions of parts based on computer vision. Machinery 55(8), 81–83 (2017)
Xie, K., Pan, W., Xu, S.X.: An underwater image enhancement algorithm for environment recognition and robot navigation. Robotics 7(1), 14 (2018)
Song, W., Wang, Y., Huang, D.M., He, Q., Wang, Z.H.: Combining background light fusion and underwater dark channel prior with color balancing for underwater image enhancement. Pattern Recognit. Artif. Intell. 31(9), 86–98 (2018)
Li, C.Y., Quo, J.C., Pang, Y.W., Chen, S.J. Wang, J.: Single underwater image restoration by blue-green channels dehazing and red channel correction. In: IEEE International Conference on Acoustics. IEEE (2016)
Guo, S.X., Chen, S.Z., Liu, F.G., Ye, X.F., Yang, H.B.: Binocular vision-based underwater ranging methods. In: 2017 IEEE International Conference on Mechatronics and Automation (ICMA). IEEE (2017)
Sheng, M.W., Zhou, H., Huang, H., Qin, H.D.: Study on an underwater binocular vision ranging method. J. Huazhong Univ. Sci. Technol. (Nat. Sci. Ed.) 46(8), 93–98 (2018)
Shi, X.C., Wang, X.J.: A ranging method in AUV underwater docking by binocular vision. Comput. Meas. Control 16(10), 1460–1462 (2008)
Archie, M., Himanshu, J.: Novelty in image reconstruction using DWT and CLAHE. Int. J. Image Graph. Signal Process. (IJIGSP) 9(5), 28–34 (2017)
Wang, H., Xu, Z.W., Xie, K., Li, J., Song, C.L.: Binocular measuring system based on OpenCV. J. Jilin Univ. (Inf. Sci. Ed.) 32(2), 188–194 (2014)
Zou, J.G., Wan, Y., Meng, L.Y.: A new Stereo matching algorithm based on adaptive weight SAD algorithm and census algorithm. Bull. Surv. Mapp. 11, 11–15 (2018)
Si, L.P., Wang, Q., Xiao, Z.L.: Matching cost fusion in dense depth recovery for camera-array via global optimization. In: 2014 International Conference on Virtual Reality and Visualization (ICVRV 2014), Shenyang, China, pp. 180–185 (2014)
Huang, S.M., Bi, Y.W., Xu, X.: Research and implementation of binocular Stereo matching algorithms. J. Ludong Univ. (Nat. Sci. Ed.) 34(1), 25–30 (2018)
Acknowledgements
This work was supported by the State Key Program of National Natural Science Foundation of China (Grant No. 61633004), the National Natural Science Foundation of China (Grant No. 41876100), the National key research and development program of China (Grant No. 2018YFC0310102 and 2017YFC0306002), the Development Project of Applied Technology in Harbin (Grant No. 2016RAXXJ071) and the Fundamental Research Funds for the Central Universities (Grant No. HEUCFP201707).
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Ye, X., Chen, H. (2019). Measurement Method of Underwater Target Based on Binocular Vision. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11742. Springer, Cham. https://doi.org/10.1007/978-3-030-27535-8_5
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DOI: https://doi.org/10.1007/978-3-030-27535-8_5
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