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Coin Counter

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:

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Coin Counter

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  1. Coin Counter Andres Uribe

  2. what • Find out the amount of money in a coin picture. $4.10

  3. How – Classifier • Build a coin classifier • Bayes Classifier • Nearest Neighbor • SVMs • Segment coins and create feature vectors

  4. 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

  5. How – Segmentation • Use of the Hough Transform to detect circles • Threshold selection to segment background

  6. 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.

  7. 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.

  8. Questions? ?

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