Abstract
In this paper, a novel image template matching approach to tackle distance measurement problem has been proposed. There are many conventional algorithms to increase the accuracy of distance measurement as reported in the literature such as Semi-global algorithm to produce the disparity map. Meanwhile, in this paper, the reverse engineering technique had been implemented to get the correct depth value by applying the image template matching method as reference for the distance measurement. The traditional algorithm to solve image matching problem take a lot of memory and computational time. Therefore, image matching problem can be considered to optimization problem and can be solved precisely. The search of the image template has been performed exhaustively by using Simulated Kalman Filter (SKF) algorithm. The experiment is conducted with a set of images taken by using stereo vision system. Experimental results show the accuracy of the distance measurement by using stereo camera, after applying (1) the estimate error model, (2) SKF and (3) PSO algorithm are 89.95%, 96.09%, 95.29% and 58.51% respectively. The limitation of estimate error model that it can only be applied into the same setup of the experiment, environment, parameters of the camera and acquired images. Instead, the proposed algorithm which is SKF can be applied to original image and image under the vision problems like illumination and partially occluded. The SKF algorithm shows more robust, more efficient and more accurate to solve the distance measurement problem.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhang, J., Wang, G.: Image matching using a bat algorithm with mutation, 203, 88–93 (2012)
Liu, X., Jiang, W., Xie, J.: An image template matching method using particle swarm optimization. In: 2009 Second Asia-Pacific Conference Computational Intelligence and Industrial Applications, pp. 83–86 (2009)
Ann, N.Q., Achmad, M.S.H., Bayuaji, L., Daud, M.R., Pebrianti, D.: Study on 3D scene reconstruction in robot navigation using stereo vision. In: 2016 IEEE International Conference on Automatic Control and Intelligent Systems, pp. 72–77 (2016)
Cui, W., He, Y.: Tournament selection based fruit fly optimization and its application in template matching, pp. 362–365 (2016)
Chidambaram, C., Lopes, H.S.: A new approach for template matching in digital images using an artificial bee colony algorithm. In: 2009 NaBIC 2009. World Congress on Nature and Biologically Inspired Computing, pp. 146–151. IEEE (2009)
Banharnsakun, A., Tanathong, S.: Object detection based on template matching through use of best-so-far ABC. Comput. Intell. Neurosci. 2014, 1–8 (2014)
Wang, Z.-F., Zheng, Z.-G.: A region based stereo matching algorithm using cooperative optimization. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE (2008)
Gong, M.: Multi-resolution stereo matching using genetic algorithm. In: Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001), pp. 21–29. IEEE Computer Society (2001)
Das, A., Bhattacharya, M.: Affine-based registration of CT and MR modality images of human brain using multiresolution approaches: comparative study on genetic algorithm and particle swarm optimization. Neural Comput. Appl. 20, 223–237 (2010)
Jiang, F., Frater, M.R., Pickering, M.: Threshold-based image segmentation through an improved particle swarm optimisation. In: 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), pp. 1–5. IEEE (2012)
Sharma, A.: Object detection in image using particle swarm optimization. Int. J. Eng. Technol. 2, 419–426 (2010)
Yao, L., Duan, H., Shao, S.: Adaptive template matching based on improved ant colony optimization. In: 2009 International Workshopon Intelligent Systems and Applications, pp. 1–4 (2009)
Ibrahim, Z., Aziz, N.H.A., Aziz, N.A.A., Razali, S., Shapiai, M.I., Nawawi, S.W., Mohamad, M.S.: A Kalman filter approach for solving unimodal optimization problems. ICIC Express Lett. 9, 3415–3422 (2015)
Mohd Azmi, K.Z., Ibrahim, Z., Pebrianti, D.: Simultaneous computation of model order and parameter estimation for ARX model based on multi-swarm particle swarm optimization. ARPN J. Eng. Appl. Sci. 10, 17191–17196 (2015)
Ibrahim, Z., Aziz, N.H.A., Aziz, N.A.A., Razali, S., Mohamad, M.S.: Simulated Kalman filter: a novel estimation-based metaheuristic optimization algorithm. Adv. Sci. Lett. 22, 2941–2946 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ann, N.Q. et al. (2018). SKF-Based Image Template Matching for Distance Measurement by Using Stereo Vision. In: Hassan, M. (eds) Intelligent Manufacturing & Mechatronics. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-8788-2_39
Download citation
DOI: https://doi.org/10.1007/978-981-10-8788-2_39
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8787-5
Online ISBN: 978-981-10-8788-2
eBook Packages: EngineeringEngineering (R0)