Money, Money, MoneyMoney, Money, Money

TEAM 6

The TEAMDana Damian ScientistInstitute: Politehnica University of TimisoaraCountry: Romania

Krisztina Dombi DocumenterInstitute: University of SzegedCountry: Hungary

Levente Sajó ProgrammerInstitute: University of Debrecen Country: Hungary

Zoltán Horváth GopherInstitute: Pannon University Country: Hungary

The Problem

The Problem: Counting money.

Input: Photo of coins (Euro\Cent perspective view,non-uniform lighting, eventual partial covering)

Task: Recognize the coins and count the total sum.

Output: The sum, and also the recognition statistics(accuracy / false positive rate etc) of the implemented method.

Difficulty: Medium

The Problem: Counting money.

Input: Photo of coins (forint with perspective view, without covering)(Let’s say we have a lot…)

Task: Recognize the coins and count the total sum.

Output: The sum, and also the recognition statistics(accuracy / false positive rate etc) of the implemented method.

Our Problem

Motivation

• In business transactions, to enable computers to recognize coins and other different forms of currency has become an essential process.

• If computers are able to do the recognition, all monetary trades and transactions will be much easier.

• Our scope is limited on recognizing only the Hungarian coins ( head OR tail ) (1F, 2F, 10F, 20F, 50F, 100F).

Monetary automates

Handy coin counter

Approach• The application is suitable for an architecture

of a coin counter system that incorporates a steady camera which monitories coins passing beneath (maybe on a belt )

Catalogue of Hungarian denomination

Theoretical background of Hough transformation

• A transformation that maps a point in a Cartesian space onto a 2D space of points, called the Hough Space

sincos yx

• Extension of the classical HT• Analytical function of a circle leads to a mapping of

each point (x, y) from the image onto a 3D Hough Space parameterized according to (a, b, r) tuple, where

– (a, b) center of the circle– r radius of the center

Points satisfying the equation are mapped into the accumulator according to the circle they belong to

Circular HT

222 )()( rbyax

Preprocessing

Enhance ContrastSharpen

Gaussian BlurSharpen

Find EdgesThresholdFill HolesOutlineInvert

Hungarian coin counter system

Input image:

Enhance Contrast

Sharpen

Gaussian Blur

Edge Detector

Threshold

Fill Holes

Outline

Invert binary

Circular Hough Transform

Detected coins

Center points and radius

Result

Core Idea

• Having a picture for training purposes, the system designs a coin table in which it stores the size of each coin

• Further recognition is based on comparison with the coin table

Main issues

• Shadows can enlarge the image of a coin, thus increasing its radius

• Different condition of illumination can generate an edge map with lack of information

• Coins are very close to each other

Limitations

• A priori knowledge of the # coins

• Dependence on the quality of edge detector

Future Plans

• Go to the Bajor söröző

• Eat good and drink a lot

• Go back to the dormitory

• Go home with lots of new experiences, new remembrance

Other Works• Coin Detector

CS7495/4495 Term ProjectDong-Shin Kim(gtg901p) CS7495Young Gyun Yun(gte257z) CS4495You-Kyung Cha(gte440y) CS4495

  • Dagobert – A New Coin Recognition and Sorting System

Michael N¨olle1, Harald Penz2, Michael Rubik2,Konrad Mayer2, Igor Holl¨ander2, Reinhard Granec2ARC Seibersdorf research GmbH1Video- and Safety Technology , 2High Performance Image ProcessingA-2444 Seibersdorf

• Design and Evaluation of Neural Networks for Coin Recognition by Using GA and SAYasue Mitsukura*, Minoru Fukumi* and Norio Akamatsu** Department of Information Science & Intelligent Systems, Faculty of EngineeringUniversity of Tokushima 2-1, Minami-josanjima, Tokushima, 770-8506 JAPAN

Thanks for your attention.

Questions? …