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**Applications**

**1. Introduction**

for the considered collections of coins.

We investigate object recognition and classification in a setting with a large number of classes as well as recognition and identification of individual objects of high similarity. Real-world data sets were obtained for the classification and identification tasks. The considered classification task is the discrimination of modern coins into several hundreds of different classes. Identification is investigated for hand-made ancient coins. Intra-class variance due to wear and abrasion vs. small inter-class variance makes the classification of modern coins challenging. For ancient coins the intra-class variance makes the identification task possible, as the appearance of individual hand-struck coins is unique. Figure 1 shows sample images

**Automatic Coin Classification and Identification** 

Reinhold Huber-Mörk1, Michael Nölle1, Michael Rubik1,

*1Department Safety and Security, Austrian Institute of Technology* 

*2Computer Vision Lab, Vienna University of Technology* 

*Austria* 

**7**

Michael Hödlmoser2, Martin Kampel2 and Sebastian Zambanini2

(a) Modern coins (b) Ancient coins

Modern coins were acquired by a high-speed machine vision system for coin sorting described in detail by Fürst et al. (2003). For ancient coins the setting is more general, images acquired

Fig. 1. Examples of images of modern and ancient coins
