Abstract
In this work we have assessed the capability of a new optimization algorithm – the Cuckoo Search algorithm in tuning the image enhancement functions for peak performance. The assessment has been conducted in comparison to two of the old optimization algorithm aided enhancement, namely, Genetic Algorithms and Particle Swarm Optimization and previous enhancement techniques Histogram Equalization and Linear Contrast Stretch techniques. Results have been assimilated in this paper and conclusions have been drawn keeping the fitness of image and number of edgels in enhanced image as the benchmark. The results have illustrated the capability of Cuckoo search algorithm in optimizing the enhancement functions.
Keywords
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References
Gorai, A., Ghosh, A.: Gray-level Image Enhancement By Particle Swarm Optimization. In: World Congress on Nature & Biologically Inspired Computing, NaBIC 2009, pp. 72–77 (2009) Print ISBN: 978-1-4244-5053-4
Munteanu, C., Rosa, A.: Towards automatic image enhancement using Genetic Algorithms. In: Proceedings of the 2000 Congress on Evolutionary Computation, vol. 2, pp. 1535–1542. Inst. Superior Tecnico, Univ. Tecnica de Lisboa, Portugal (2000)
Braik, M., Sheta, A.F., Ayesh, A.: Image Enhancement Using Particle Swarm Optimization. In: Proceedings of the World Congress on Engineering, WCE 2007, London, U.K, July 2-4, vol. I (2007) ISBN:978-988-98671-5-7
Singh, N., Kaur, M., Singh, K.V.P.: Parameter Optimization In Image Enhancement Using PSO. American Journal of Engineering Research (AJER) 2(5), 84–90, e-ISSN : 2320-0847 p-ISSN : 2320-0936
Yang, X.-S., Deb, S.: Cuckoo search via Lévy flights. In: Proc. of World Congress on Nature & Biologically Inspired Computing (NaBIC 2009), India, pp. 210–214. IEEE Publications, USA (2009)
Yang, X.-S., Deb, S.: Engineering Optimisation by Cuckoo Search. Int. J. Mathematical Modelling and Numerical Optimisation 1(4), 330–343 (2010)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall Publications
Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing using MATLAB, 2nd edn. Prentice Hall
Mantegna, R.N.: Fast, accurate algorithm for numerical simulation of Lévy stable stochastic processes. Phys. Rev. E 49(5), 4677–4683 (1994), doi:10.1103/PhysRevE.49.4677 Key: citeulike: 6592204
He, Y., Tian, J., Luo, X., Zhang, T.: Image enhancement and minutiae matching in fingerprint verification. Elsevier, Pattern Recognition Letters 24(9-10), 1349–1360 (2003)
Sezan, M.I., Tekalp, A.M., Schaetzing, R.: Automatic anatomically selective image enhancement in digital chest radiography. IEEE Trans. Med. Imag. 8, 154–162 (1989)
Pratt, W.K.: Digital Image Processing, 2nd edn. John Wiley and Sons (1991)
Castleman, K.R.: Digital Image Processing. Prentice Hall (1996)
Chaudhary, A., Vatwani, K., Agrawal, T., Raheja, J.L.: A Vision-Based Method to Find Fingertips in a Closed Hand. Journal of Information Processing Systems 8(3), 399–408 (2012)
Hong, L., Wan, Y., Jain, A.: Fingerprint image enhancement: algorithm and performance evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(8) (August 1998)
Senthilnath, J.: Clustering Using Levy Flight Cuckoo Search. In: Proceedings of Seventh International Conference on Bio-Inspired Computing, vol. 202, pp. 65–75 (2013)
Saida, I.B., Nadjet, K., Omar, B.: A new algorithm for data clustering based on cuckoo search optimization. In: Pan, J.-S., Krömer, P., Snášel, V. (eds.) Genetic and Evolutionary Computing. AISC, vol. 238, pp. 55–64. Springer, Heidelberg (2014)
Rodrigues, D., Pereira, L.A.M., Almeida, T.N.S., Papa, J.P., Souza, A.N., Ramos, C.C.O., Yang, X.-S.: BCS: A Binary Cuckoo Search algorithm for feature selection. In: 2013 IEEE International Symposium on Circuits and Systems (ISCAS), May 19-23, pp. 465–468 (May 2013), doi:10.1109/ISCAS.2013.6571881
Pani, P.R., Nagpal, R.K., Malik, R., Gupta, N.: Design of planar EBG structures using cuckoo search algorithm for power/ground noise suppression. Progress In Electromagnetics Research M 28, 145–155 (2013), doi:10.2528/PIERM12121108
Aly, W.M., Sheta, A.: Parameter Estimation of Nonlinear Systems Using Lèvy Flight Cuckoo Search. Research and Development in Intelligent Systems XXX, 443–449 (2013), doi:10.1007/978-3-319-02621-3_33
Goel, S., Sharma, A., Bedi, P.: Journal Title - International Journal of Hybrid Intelligent Systems. Novel approaches for classification based on Cuckoo Search Strategy 10(3), 107–116 (2013), doi:10.3233/HIS-130169 (Issue Cover Date January 1, 2013)
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Ghosh, S., Roy, S., Kumar, U., Mallick, A. (2014). Gray Level Image Enhancement Using Cuckoo Search Algorithm. In: Thampi, S., Gelbukh, A., Mukhopadhyay, J. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-04960-1_25
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DOI: https://doi.org/10.1007/978-3-319-04960-1_25
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04959-5
Online ISBN: 978-3-319-04960-1
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