Abstract
An improved particle swarm optimization algorithm, CSPSO (Chaotic Species-based particle swarm optimization), is proposed for solving the template matching problem. Template matching is one of the image comparison techniques widely applied to component existence checking in the printed circuit board (PCB) and electronics assembly industries. The proposed approach adopts the special nonlinear characteristic and ergodicity of chaos to enrich the search ability of the species-based particle swarm optimization (SPSO). To test its performance, the proposed CSPSO-based approach is compared with SPSO-based approach using two experimental studies. The CSPSO-based approach is proven to be superior to the original SPSO-based one in term of efficiency.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Gavrila, D.M.: Pedestrian Detection from a Moving Vehicle. In: 6th European Conf. on Computer Vision, vol. II, pp. 37–49. Springer, Heidelberg (2000)
Toyama, K., Blake, A.: Probabilistic Tracking in a Metric Space. In: 8th IEEE International Conference on Computer Vision, vol. II, pp. 50–57. IEEE Press, New York (2001)
Crispin, A.J., Rankov, V.: Automated Inspection of PCB Components Using a Genetic Algorithm Template-matching Approach. Int. J. Adv. Manuf. Tech. 35, 293–300 (2007)
Athitsos, V., Sclaroff, S.: An Appearance-based Framework for 3D Hand Shape Classification and Camera Viewpoint Estimation. In: IEEE Conf. on FGR, pp. 45–50. IEEE Press, New York (2002)
Shakhnarovich, G., Viola, P., Darrell, T.: Fast Pose Estimation with Parameter-sensitive Hashing. In: 9th IEEE Int. Conf. on Computer Vision, vol. II, pp. 750–757. IEEE Press, New York (2003)
Stenger, B., Thayananthan, A., Torr, P.H.S., Cipolla, R.: Filtering Using a Tree-based Estimator. In: 9th IEEE Int. Conf. on Computer Vision, vol. II, pp. 1063–1070. IEEE Press, New York (2003)
Olson, C.F., Huttenlocher, D.P.: Automatic Target Recognition by Matching Oriented Edge Pixels. IEEE T. Image Process. 6(1), 103–113 (1997)
Borenstein, E., Ullman, S.: Class-specific, Top-down Segmentation. In: 7th European Conf. on Computer Vision, vol. I, pp. 109–122. Springer, Heidelberg (2002)
Triesch, J., Von der Malsburg, C.: A System for Person-independent Hand Posture Recognition Against Complex Backgrounds. IEEE T. Pattern Analysis and Machine Intell. 23(12), 1449–1453 (2001)
Hewer, G., Kenney, C., Hanson, G., Wei, K., Peterson, L.: Detection of Small Objects Using Adaptive Wavelet-based Template Matching. In: SPIE Proceedings of Signal and data processing of small targets, vol. 3809, pp. 95–106. SPIE, Bellingham (1999)
Krattenthaler, W., Mayer, K.J., Zeiler, M.: Point Correlation: A Reduced-cost Template Matching Technique. In: 1st IEEE Int. Conf. on Image Processing, vol. I, pp. 208–212. IEEE Press, New York (1994)
Rosenfeld, A., Vanderburg, G.J.: Coarse-Fine Template Matching. IEEE T. Sys., Man and Cyb. 7, 104–197 (1977)
Wang, D.Z., Wu, C.H., Ip, A., Chan, C.Y., Wang, D.W.: Fast Multi-template Matching Using a Particle Swarm Optimization Algorithm for PCB Inspection. In: Giacobini, M., Brabazon, A., Cagnoni, S., Di Caro, G.A., Drechsler, R., Ekárt, A., Esparcia-Alcázar, A.I., Farooq, M., Fink, A., McCormack, J., O’Neill, M., Romero, J., Rothlauf, F., Squillero, G., Uyar, A.Ş., Yang, S. (eds.) EvoWorkshops 2008. LNCS, vol. 4974, pp. 365–370. Springer, Heidelberg (2008)
Moganti, M., Ercal, F., Dagli, C.H., Tsunekawa, S.: Automated PCB Inspection Algorithms: a Survey. Comput. Vis. Image Underst. 63(2), 287–313 (1996)
Li, D., Yu, C.F.: The Application of Genetic Algorithm in Detecting Printed Circuit Board Components. Journal of Fudan University (Natural Science) 45(4), 452–456 (2006)
Liu, B., Wang, L., Jin, Y.H., Tang, F., Huang, D.X.: Improved Particle Swarm Optimization Combined with Chaos. Chaos Soliton Fract. 25, 1261–1271 (2005)
Beasle, D., Bull, D.R., Martin, R.R.: A Sequential Nitche Technique for Multimodal Function. Evol. Comput. 1(2), 101–125 (1993)
Ling, Q., Wu, G., Wang, Q.: Restricted Evolution Based Multimodal Function Optimization in Holographic Grating Design. In: IEEE Congress on Evolutionary Computation 2005, pp. 789–794. IEEE Press, München (2005)
Kennedy, J., Eberhart, R.: Swarm Intelligence. Morgan Kaufmann Academic Press, San Francisco (2001)
Li, X.: Adaptively Choosing Neighbourhood Bests Using Species in a Particle Swarm Optimizer for Multimodal Function Optimization. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 105–116. Springer, Heidelberg (2004)
Zhang, H., Shen, J.H., Zhang, T.N., Li, Y.: An Improved Chaotic Particle Swarm Optimization and Its Application in Investment. In: International Symposium on Computational Intelligence and Design, vol. 1, pp. 124–128 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, C., Dong, N., Ip, W., Chen, Z., Yung, K. (2009). Applying Chaotic Particle Swarm Optimization to the Template Matching Problem. In: Cai, Z., Li, Z., Kang, Z., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2009. Lecture Notes in Computer Science, vol 5821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04843-2_44
Download citation
DOI: https://doi.org/10.1007/978-3-642-04843-2_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04842-5
Online ISBN: 978-3-642-04843-2
eBook Packages: Computer ScienceComputer Science (R0)