Abstract
According to the problem of spliced money in ATM (Automatic Teller Machine), the paper puts forward a template matching algorithm for recognition of left and right numbers based on one-dimensional gray scale projection. First it uses the Canny boundary detection algorithm to separate the banknote boundary from the R component image, and then preprocesses the image to make the subsequent processing easier; secondly applies the predefined location to divide the area of left and right numbers; thirdly calculates the one-dimensional gray scale projection curves of left and right numbers, based on which every character or number is divided; finally carries out the operation of template matching to obtain correlation coefficients of every character or number, comparing which with threshold it judges whether the left and right numbers are matched. For the transparent tape attached to the spliced money, a method based on the difference in object reflectivity to recognize the tape is designed. First it highlights the characteristics of the tape by preprocessing and binary morphological analysis of the B component image. Finally, it judges whether there is transparent tape on the surface of the banknote according to the set threshold value. Experimental results show that both number matching and tape detection can be completed, and algorithm can correctly recognize spliced money. The correct recognition rate of the algorithm reaches 100%, and the false positive rate、false negative rate are both 0. The processing is fast and simple, which meets the requirements of ATM.
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References
Ashiba HI, Mansour HM, Ahmed HM (2018) Enhancement of infrared images based on efficient histogram processing. Wirel Pers Commun 99(2):619–636
Athar A, Osama S (2018) Quality enhancement of infrared images using dynamic fuzzy histogram equalization and high pass adaptation in DWT. Optik-International Journal for Light and Electron Optics 160(12):146–158
Chen H, Zhao Y, Geng Y (2012) Stereo matching based on adaptive support-weight approach in RGB vector space. Appl Opt 51(16):3538–3545
Chen Z, Wang X, Sun Z, Wang Z (2016) Motion saliency detection using a temporal fourier transform. Opt Laser Technol 80(3):1–15
Chen Y, Xu W, Zuo J, Yang K (2019) The fire recognition algorithm using dynamic feature fusion and IV-SVM classifier. Clust Comput 22(S3):7665–7675. https://doi.org/10.1007/s10586-018-2368-8
Chen Y, Wang J, Liu S et al (2019) Multiscale fast correlation filtering tracking algorithm based on a feature fusion model. Concurrency and Computation: Practice and Experience. https://doi.org/10.1002/cpe.5533
Chen Y, Wang J, Xia R, Zhang Q, Cao Z, Yang K (2019) The visual object tracking algorithm research based on adaptive combination kernel. J Ambient Intell Humaniz Comput 10:4855–4867
Chen Y, Xiong J, Xu W, Zuo J (2019) A novel online incremental and decremental learning algorithm based on variable support vector machine. Clust Comput 22(S3):7435–7445. https://doi.org/10.1007/s10586-018-1772-4
Chen Y, Wang J, Chen X, Zhu M, Yang K, Wang Z, Xia R (2019) Single-image super-resolution algorithm based on structural self-similarity and deformation block features. IEEE Access 7:58791–58801
Chen Y, Wang J, Chen X, Sangaiah AK, Yang K, Cao Z (2019) Image super-resolution algorithm based on dual-channel convolutional neural networks. Appl Sci 9(11):2316. https://doi.org/10.3390/app9112316
Chen Y, Tao J, Liu L, Xiong J, Xia R, Xie J, Zhang Q, Yang K (2020) Research of improving semantic image segmentation based on a feature fusion model. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-02066-z
Chen Y, Tao J, Zhang Q, Yang K, Chen X, Xiong J, Xia R, Xie J (2020) Saliency detection via improved hierarchical principle component analysis method. Wirel Commun Mob Comput 6:1–12. https://doi.org/10.1155/2020/8822777
Chen Y, Liu L, Tao J, Xia R, Zhang Q, Yang K, Xiong J, Chen X (2020) The improved image inpainting algorithm via encoder and similarity constraint. Vis Comput. https://doi.org/10.1007/s00371-020-01932-3
Cutting out real money and sticking it to fake money, beware of RMB 100 "spliced money". http://www.creditqhd.gov.cn/article-details/fxts/4a4cb1e3-f418-426b-8a5e-da24258eec90 2020.3.
Half real and half fake “spliced money”. https://baike.baidu.com/item/%E6%8B%BC%E6%8E%A5%E5%B8%81/4412658?fr=aladdin 2016.4.
Jenifer S, Parasuraman S, Kadirvelu A (2016) Contrast enhancement and brightness preserving of digital mammograms using fuzzy clipped contrast-limited adaptive histogram equalization algorithm. Appl Soft Comput 42(3):167–177
Joanna I O (2013) Efficient optical character recognition system for automatic soccer player's identification. Proceedings of the Computer Analysis of Images and Patterns workshop. http://eprints.hud.ac.uk/id/eprint/18122/
Joanna IO (2015) Active contour based optical character recognition for automated scene understanding. Neuro computing 161:65–71. https://doi.org/10.1016/j.neucom.2014.12.089
Joanna I O (2019) Designing transparent and autonomous intelligent vision systems. Proceedings of the 11th International Conference on Agents and Artificial Intelligence. https://doi.org/10.5220/0007585208500856
Li Y, Yan Y (2019) Study of infrared image enhancement based on histogram equalization and fuzzy set theory. Computer & Digital Engineering 22(2):428–430
Li D, Li J, Sun L (2002) Design and realization of communication between biller and vending machine. Journal of Northern Jiaotong University 26(6):80–82
Li C, Huang R, Ding Z, Gatenby JC, Metaxas DN, Gore JC (2011) A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI. IEEE Trans Image Process 20(7):2007–2017
Liao Z, Zhang R, He S, Zeng D, Wang J, Kim HJ (2019) Deep learning-based data storage for low latency in data center networks. IEEE Access 7:26411–26417
Liu C, Lin W, Hu X et al (2009) Research on technology of identifying the counterfeit based on texture recognition. Laser & Infrared 39(6):685–687
Lu W, Zhang X, Lu H, Li F (2020) Deep hierarchical encoding model for sentence semantic matching. J Vis Commun Image Represent 71:102794. https://doi.org/10.1016/j.jvcir.2020.102794
Luo Y, Qin J, Xiang X, Tan Y, Liu Q, Xiang L (2020) Coverless real-time image information hiding based on image block matching and dense convolutional network. J Real-Time Image Proc 17(1):125–135
Mao G (2017) Research on the steel tube defects on-line monitoring algorithm based on image processing. J Geom 35(2):62–66
Min H, Jia W, Wang X et al (2014) An intensity-texture model based level set method for image segmentation. Pattern Recogn 48(4):1547–1562
Mohamed B, Amar M, Ismail B (2011) Multiregion image segmentation by parametric kernel graph cuts. IEEE Trans Image Process 20(2):545–557
Ren Q (2017) License plate recognition technology based on digital image processing. China Strategic Emerging Industry 40(2):118–121
The owner of the supermarket received a bill of RMB 100 and found out a few days later that it was "spliced money" https://henan.qq.com/a/20170117/010907.htm 2017.1.
Wan M, Gu G, Maldague et al (2018) Particle swarm optimization-based local entropy weighted histogram equalization for infrared image enhancement. Infrared Physics 91(12):164–181
Wang H, Gao G, Xu L et al (2018) A multi-region level set model based on texture feature for image segmentation. Acta Electron Sin 46(11):2588–2596
Wang J, Qin J, Xiang X, Tan Y, Pan N, College of Computer Science and Information Technology, Central South University of Forestry and Technology, 498 shaoshan S Rd, Changsha, 410004, China (2020) CAPTCHA recognition based on deep convolutional neural network. Math Biosci Eng 16(5):5851–5861. https://doi.org/10.3934/mbe.2019292
Yang S, Long Y, Yao G et al (2019) Research on image based on target region segmentation algorithm. Electronic Engineering & Product World 20(2):64–68
Yin X, Zhang M, Wang L, Liu Y (2020) Interface debonding performance of precast segmental nano-materials based concrete (PSNBC) beams. Mater Express 10:1317–1327
Zhang J, Wu Y, Feng W et al (2019) Spatially attentive visual tracking using multi-model adaptive response fusion. IEEE access PP(99):1-1·
Zhang J, Zhong S, Wang T et al (2020) Blockchain-based systems and applications: a survey. Journal of Internet Technology 21(1):1–14. https://doi.org/10.3966/160792642020012101001
Author’s information
Wang Zhiyang (1982 -), male (Hui nationality), born in Bengbu, Anhui Province(China), obtained his bachelor’s and master’s degrees from Harbin Institute of Technology,associate professor of Anhui Vocational College of Electronics & Information Technology, research direction: image processing, pattern recognition, E-mail:181566286@qq.com
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Key projects of excellent young talents support plan in colleges and universities of Anhui Province (gxyqZD2020073).
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This work was supported by Department of Education of Anhui Province (China) and Anhui Vocational College of Electronics & Information technology.
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Wang, Z. An algorithm for ATM recognition of spliced money based on image features. Multimed Tools Appl 80, 11471–11489 (2021). https://doi.org/10.1007/s11042-020-10348-z
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DOI: https://doi.org/10.1007/s11042-020-10348-z