Abstract
With the rapid development of society, the requirements and standards of image recognition are getting higher and higher. Therefore, applying some new technologies to image recognition has become an extremely important research topic. In this study, based on the grey relational analysis method, the face image was taken as the main research subject, an image recognition model based on the grey relational analysis method was established, and the related experimental results were obtained. Compared with the traditional face image recognition system, the image recognition method based on the grey relational analysis method had higher recognition speed and good recognition performance. This study provides a new path for the research of image recognition.
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REFERENCES
Lawgaly, A., Khelifi, F., and Bouridane, A., Image sharpening for efficient source camera identification based on sensor pattern noise estimation, IEEE 2013 Fourth International Conference on Emerging Security Technologies, 2013, pp. 113–116.
Pah, N.D., Image-based distance change identification by segment correlation, Proceedings of Second International Conference on Electrical Systems, Technology and Information 2015 (ICESTI 2015), Singapore, 2016.
Chen, L. and Hassanpour, N., Survey: How good are the current advances in image set based face identification?—Experiments on three popular benchmarks with a naïve approach, Comput. Vision Image Understanding, 2017, vol. 160, pp. 1–23.
Qiao, B., Jin, L., and Yang, Y., An adaptive algorithm for Grey image edge detection based on Grey correlation analysis, International Conference on Computational Intelligence & Security, 2017.
Ding, Z., Qian, S., Li, Y.L., and Li, Z.H., An image matching method based on the analysis of Grey correlation degree and feature points, Aerosp. Electron. Conf., 2015.
Thepade, S., Das, R., and Ghosh, S., Novel technique in block truncation coding based feature extraction for content based image identification, Lect. Notes Comput. Sci., 2015, vol. 25, pp. 55–76.
Wang, J.N., Chen, X.L., Hou, X.W., Zhou, L.B., Zhu, C.D., and Ji, L.Q., Construction, implementation and testing of an image identification system using computer vision methods for fruit flies with economic importance (Diptera: Tephritidae), Pest Manage. Sci., 2016, vol. 73, no. 7, pp. 1511–1528.
Li, X., Liao, X., Tan, X., and Wang, H., Using Grey relational analysis to evaluate resource configuration and service ability for hospital on public private partnership model in China, Proceedings of 2013 IEEE International Conference on Grey systems and Intelligent Services (GSIS), 2014.
Lu, J., Chen, P., Shen, J., Liang, Z., and Yang, H., Study on the prediction of gas content based on Grey relational analysis and BP neural network, Proceedings of the Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), Berlin–Heidelberg, 2013.
Anand, G., Alagumurthi, N., Elansezhian, R., Palanikumar, K., and Narayanan, V., Investigation of drilling parameters on hybrid polymer composites using Grey relational analysis, regression, fuzzy logic, and ANN models, J. Braz. Soc. Mech. Sci. Eng., 2018, vol. 40, no. 4, p. 214.
Ying, K.D., Zhang, Y., and Li, X.M., Research on storm-tide disaster losses in China using a new Grey relational analysis model with the dispersion of panel data, Int. J. Environ. Res. Public Health, 2017, vol. 14, no. 11, p. 1330.
Prasad, K.S., Chalamalasetti, S.R., and Damera, N.R., Application of Grey relational analysis for optimizing weld bead geometry parameters of pulsed current micro plasma arc welded Inconel, Int. J. Adv. Manuf. Technol., 2015, vol. 78, nos. 1–4, pp. 625–632.
Chinnaiyan, P. and Jeevanantham, A.K., Multi-objective optimization of single point incremental sheet forming of AA5052 using Taguchi based Grey relational analysis coupled with principal component analysis, Int. J. Precis. Eng. Manuf., 2014, vol. 15, no. 11, pp. 2309–2316.
Konganapuram Sundararajan, S. and Shanmugam, S.K., Multi-objective optimization of friction welding process parameters using Grey relational analysis for joining aluminium metal matrix composite, Mater. Sci., 2018, vol. 24, no. 2.
Pandey, A.K. and Gautam, G.D., Grey relational analysis-based genetic algorithm optimization of electrical discharge drilling of Nimonic-90 superalloy, J. Braz. Soc. Mech. Sci. Eng., 2018, vol. 40, no. 3, p. 117.
Wang, L., Yin, K., Cao, Y., and Li, X., A new Grey relational analysis model based on the characteristic of inscribed core (IC-GRA) and its application on seven-pilot carbon trading markets of China, Int. J. Environ. Res. Public Health, 2018, vol. 16, no. 1.
Bhatt, R.J. and Raval, H.K., Investigation on flow forming process using Taguchi-based Grey relational analysis (GRA) through experiments and finite element analysis (FEA), J. Braz. Soc. Mech. Sci. Eng., 2018, vol. 40, no. 11.
Javed, S.A., Mahmoudi, A., and Khan, A.M., Investigation of drilling parameters on hybrid polymer composites using Grey relational analysis, regression, fuzzy logic, and ANN models: A critical note, J. Braz. Soc. Mech. Sci. Eng., 2018, vol. 40, no. 12.
Hai, N. and Fang, W., Evaluation of the naval fleet’s communication system based on Grey relational analysis method, IEEE 2017 9th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), Changsha, 2017, pp. 177–181.
Bagherian, A.R., Teimouri, R., Ghasemi Baboly, M., and Leseman, Z., Application of Taguchi, ANFIS and Grey relational analysis for studying, modeling and optimization of wire EDM process while using gaseous media, Int. J. Adv. Manuf. Technol., 2014, vol. 71, nos. 1–4, pp. 279–295.
Ding, C., Xu, C., and Tao, D., Multi-task pose-invariant face recognition, IEEE Trans. Image Process., 2015, vol. 24, no. 3, pp. 980–993.
Nguyen, D.T., Pham, T.D., Baek, N.R., and Park, K.R., Combining deep and handcrafted image features for presentation attack detection in face recognition systems using visible-light camera sensors, Sensors, 2018, vol. 18, no. 3, p. 699.
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This work is supported by Scientific Research Foundation of Shangluo University: Research on Real Time Image Enhancement Based on FPGA (Project number: 16SKY007).
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Hua Li Application of Image Recognition Based on Grey Relational Analysis. Aut. Control Comp. Sci. 54, 371–377 (2020). https://doi.org/10.3103/S0146411620040070
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DOI: https://doi.org/10.3103/S0146411620040070