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Proceedings ArticleDOI

Embedded System for Cash Deposit in ATM

TL;DR: The proposed Embedded System for Cash Deposit at ATM machine will be installed in the ATM machines already available and will enable customers to deposit money into their account without going to bank.
Abstract: In this paper, an Embedded System for Cash Deposit at ATM machine has been proposed. ATMs available nowadays facilitate services like cash withdrawal, transaction details, account balance, card to card money transfer. The proposed system will be installed in the ATM machines already available and will enable customers to deposit money into their account without going to bank. This system consists of currency Recognizer and Currency Counter and User interface. This system will facilitate customers to deposit cash at ATM available in their locality.
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Journal ArticleDOI
TL;DR: A coarse-to-fine approximation of the original template using a diffusion-like equation is used to create a library of templates which can successively perform minimizations which are locally well-behaved.
Abstract: We examine the problem of locating an object in an image when size and rotation are unknown. Previous work has shown that with known geometric parameters, an image restoration method can be useful by estimating a delta function at the object location. When the geometric parameters are unknown, this method becomes impractical because the likelihood surface to be minimized across size and rotation has numerous local minima and areas of zero gradient. We propose a new approach where a smooth approximation of the template is used to minimize a well-behaved likelihood surface. A coarse-to-fine approximation of the original template using a diffusion-like equation is used to create a library of templates. Using this library, we can successively perform minimizations which are locally well-behaved. As detail is added to the template, the likelihood surface gains local minima, but previous estimates place us within a well-behaved "bowl" around the global minimum, leading to an accurate estimate. Numerical experiments are shown which verify the value of this approach for a wide range of values of the geometric parameters.

105 citations

Proceedings ArticleDOI
01 Dec 2014
TL;DR: The proposed approach identifies denomination by extracting features like Center Numeral, Shape, RBI Seal, Latent Image and Micro Letter by using a similarity based classifier to predict test sample.
Abstract: Currency recognition system is one of the fast growing research fields under image processing This paper proposes a novel method for Indian currency recognition Our proposed approach identifies denomination by extracting features like Center Numeral, Shape, RBI Seal, Latent Image and Micro Letter Principal Component Analysis is used to reduce the dimensions and a similarity based classifier is constructed to predict test sample Results are also validated by constructing models using classifier implemented using WEKA and testing with unseen samples not considered in feature extraction Our study demonstrated that center numeral results in an accuracy of 100% with all family of currencies

23 citations

Proceedings ArticleDOI
Hiroshi Sako1, T. Miyatake1
23 Aug 2004
TL;DR: Several image-recognition techniques that can provide the important functions required by advanced-intelligent automated teller machines (AI-ATMs) are described, including banknote image processing, form processing and character recognition, and biometric techniques.
Abstract: Several image-recognition techniques that can provide the important functions required by advanced-intelligent automated teller machines (AI-ATMs) are described. These functions are (1) basic cash handling such as withdrawal and deposit of money, (2) handling remittance forms and cheques, (3) delivering information as an "information KIOSK", and (4) security maintenance such as identification of users and surveillance of the ATM environment. The image-recognition techniques for realising these AI-ATM functions are (1) banknote image processing, (2) form processing and character recognition, (3) intention recognition, and (4) biometric techniques.

10 citations