Abstract
For the complex and changeable recording scene and lighting condition, which makes images uneven in light and short of contrast ratio, a linear transform image enhancement method based on HSV color space transform is proposed to improve the image quality. In order to maintain the image color invariant, firstly conversing the traditional RGB color space to HSV color space, then analyzing the relationship of S and V components between the HSV color space model and license plate colors, calculating linear factor and in making use of the relationship between the components, α and γ adjusting the coefficients, finally conversing the HSV model parameters to RGB space. The experimental results show that, compared with the bidirectional histogram equalization method and the Retinex method, the proposed method can be effectively used in the image enhancement for driving recorder, not only enhanced in contrast and bright of the license plate region, and has the strong realtime processing capability.
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References
Vernay, M., Castetbon, K., et al.: Hercberg. Intelligent transportation systems. In: Neurocomputing, vol.73, pp.591-592 (2010)
Xie, A.: A. Development of intelligent vehicle traveling data recorder. Automobile Parts (2010)
Zhao, Y., Fu, X., et al.: A new image enhancement algorithm for low illumination environment. Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on. IEEE, pp.625-627 (2011)
Yoo, Y., Im, J., Paik, J.: Low-Light image enhancement using adaptive digital. Pixel Binning. Sensors vol.15, pp.14917-14931 (2015)
Mishra, N., Kumar, P.S., Chandrakanth, R., et al.: Image enhancement using logarithmic image processing model. Iete Journal of Research. vol.46, pp.309-313 (2015)
Yu, Q., Ma, S.Q., Ma, D.M.: Maintaining image brightness adaptive local contrast enhancement. Computer Engineering and Applications, vol. 7, pp. 160-164 (2015)
Zhang, L.B., Ge, M.L.: A kind of image enhancement algorithms combination of spatial and transform domain. Electronics Optics and Control, vol. 12, pp. 45-48, (2014)
Qin,X.J., et al: Retinex Structured Light Image Enhancement Algorithms in HSV Color Space. Journal of Computer-Aided Design and Computer Graphics, vol.4, pp. 488-493. (2013)
Chen, C.,: Improved single scale retinex algorithm in image enhancement. Computer Applications and Software, vol. 4, pp. 55-57. (2013)
Zhan, K., Teng, J., Shi, J., et al.: Feature-linking model for image enhancement. Neural Computation, pp. 1-29. (2016)
Wang, S., Li, B., Zheng, J.,: Parameter-adaptive nighttime image enhancement with multi-scale decomposition. Iet Computer Vision. (2016)
Centeno, J.A.S., Haertel, V.: An adaptive image enhancement algorithm. Pattern Recognition, vol. 30(7), pp. 1183-1189. (2014)
Qin,X.J., et al: Retinex Structured Light Image Enhancement Algorithms in HSV Color Space. Journal of Computer-Aided Design and Computer Graphics, vol.4, pp. 488-493. (2013)
Li, Y., Hu, J., Jia, Y.: Automatic SAR image enhancement based on nonsubsampled contourlet transform and memetic algorithm. Neurocomputing, vol. 134(9), pp. 70-78. (2014)
Lee, J., Pant, S.R., Lee, H.S.: An adaptive histogram equalization based local technique for contrast preserving image enhancement. International Journal of Fuzzy Logic and Intelligent Systems, vol. 15(1), pp. 35-44. (2015)
Prema, S., Shenbagavalli, A.: Image enhancement based on clustering. International Journal of Applied Engineering Research, vol. 10(20), pp. 17367-17371. (2015)
Dong, Y.B., Li, M.J., Sun, Y.: Analysis and comparison of image enhancement methods. Applied Mechanics and Materials, pp. 1593-1596. (2015)
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Zhang, M., Zou, F., Zheng, J. (2017). The Linear Transformation Image Enhancement Algorithm Based on HSV Color Space. In: Pan, JS., Tsai, PW., Huang, HC. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 64. Springer, Cham. https://doi.org/10.1007/978-3-319-50212-0_3
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DOI: https://doi.org/10.1007/978-3-319-50212-0_3
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