The design of HMM-based banknote recognition system

Gai, Shan; Liu, Peng; Liu, Jiafeng; Tang, Xianglong

doi:10.1109/icicisys.2009.5357719

Cited by 7 publications

(2 citation statements)

References 7 publications

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“…There have been a number of papers that focus on the general banknote recognition problem (Gai, Liu, Liu & Tang, 2009;Nishimura, 2009;Kim, Lee, Suhngm, Ryu & Lee, 2013;Ahangaryan, Mohammadpour & Kianisarkaleh, 2012;Wu, Zhang, Ma, Wang & Jin, 2009;Lee & Kim, 2003;Sun & Li, 2008;Wu, Zhang & Liu, 2012;Omatu, Yoshioka & Kosaka 2009;Jin, Song, Tang & Du, 2008;Qian, Qian & Zhang, 2006;Sako & Miyatake, 2004;Takeda & Nishikage, 2000;Sajal, Kamruzzaman & Jewel, 2008;Lee, Jang, Oh & Yu, 2011;Qian, Zuo, He, Tian & Zhang, 2011;Hassanpour & Farahabadi, 2009;Jahangir & Chowdhury, 2007;Kosaka, Omatsu & Fujinaka, 2001) without considering the blind as users.…”

Section: Related Workmentioning

confidence: 99%

Reliable and User Friendly U.S Banknote Recognition Application for Visually Impaired Users on Android Smartphones

Yang

Schafer

Ganz

2014

International Journal of E-Health and Medical Communications

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This paper introduces a reliable and user-friendly Android application that helps visually impaired users recognize U.S banknotes. The application relies only on an Android Smartphone and does not require any wireless data connection or back-end infrastructure. The application is proven to be robust and reliable under various environmental conditions which differ in lighting and background conditions. The overall banknote detection accuracy is over 94% in any lighting conditions (even in a dark room) or backgrounds with near real-time banknote detection time of 7 seconds. The main contribution of this paper is the use of a robust and reliable computer vision algorithm on the Android platform combined with a friendly “vision free” user interface.

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Section: Related Workmentioning

confidence: 99%

Reliable and User Friendly U.S Banknote Recognition Application for Visually Impaired Users on Android Smartphones

Yang

Schafer

Ganz

2014

International Journal of E-Health and Medical Communications

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“…The object simulated image signal is acquired by CIS image sensor, which converts the signal into the electrical signal. The amplified analog signal is converted into the standard digital signal by analog-digital converter AD9822 and then sent to CPLD cache and finally input to the DSP RAM via EDMA channel for image processing and identification in DSP [3].…”

Section: Working Principle Of Image Acquisition Systemmentioning

confidence: 99%

Image Acquisition Method Based on TMS320DM642

Liu

2013

AMM

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A method of the image acquisition based on digital signal processor (DSP) is introduced. DSP, complex programmable logic device (CPLD) and contact image sensor (CIS) are combined in the hardware design, and the time-sequence analysis of the image acquisition process is also presented. Practical application indicates that this method has high accuracy and is rapid enough to satisfy the requirement of real-time acquisition.

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Currency security and forensics: a survey

Chambers

Yan

Garhwal

et al. 2014

Multimed Tools Appl

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Abstract-By its definition, the word 'currency' refers to an agreed medium for exchange, a nation's currency is the formal medium enforced by the elected governing entity. Throughout history, issuers have faced one common threat: counterfeiting. Despite technological advancements, overcoming counterfeit production remains a distant future. Scientific determination of authenticity requires a deep understanding of the raw materials and manufacturing processes involved. This survey serves as a synthesis of the current literature to understand the technology and the mechanics involved in currency manufacture and security, whilst identifying gaps in the current literature. Ultimately, a robust currency is desired.

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The design of HMM-based banknote recognition system

Cited by 7 publications

References 7 publications

Reliable and User Friendly U.S Banknote Recognition Application for Visually Impaired Users on Android Smartphones

Reliable and User Friendly U.S Banknote Recognition Application for Visually Impaired Users on Android Smartphones

Image Acquisition Method Based on TMS320DM642

Currency security and forensics: a survey

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