Coin Counter

Andres Uribe

what

• Find out the amount of money in a coin picture.

$4.10

How – Classifier

• Build a coin classifier– Bayes Classifier– Nearest Neighbor– SVMs

• Segment coins and create feature vectors

How - DATA

• 80 images of standard US coins.• 10 for each class:– Quarter: front and back– Dime: front and back– Nickel: front and back– Penny: front and back

How – Segmentation

– Use of the Hough Transform to detect circles– Threshold selection to segment background

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How – Features

– Radial edge distribution:• Detect edges in the coin image• Construct a normalized edge radial histogram with 2, 4,

8, 16 and 32 bins.

Results

– Classifier:• Bayes: 72.5%• SVM: yet to be implemented.• NNR: yet to be implemented.

– Money counter:• First approach uses too much memory for the circle

detection.• Will use the best performing classifier.

Questions?

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