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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: - PowerPoint PPT Presentation
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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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