README.TXT=============================================files:showCoinSeg.m     displays segmentation resultimg1.png          test coin imagereadme.txt        this filesegScaleAccHT.m   coin segmentation functionsegScaleAccHT.pdf algorithm documentationtestSegHT.m       demo scriptproperties:* only 1 coin per image allowed* only circular coins allowed* image background may be texturedimg1.png stems from the small MUSCLE CIS Seibersdorftest dataset.Version 1.1Date: April 25 2008(C)opyright Christian Kotz 2007/2008Algorithms is similar to coin segmentation algorithm in:@INPROCEEDINGS{Reisert2006,  author = {Marco Reisert and Olaf Ronneberger and Hans Burkhardt},  title = {An Efficient Gradient Based Registration Technique for Coin Recognition},  year = {2006},  booktitle = {Proceedings of the MUSCLE CIS Coin Competition Workshop},  pages = {19--31},  booktitleaddon = {September 11, 2006},  venue = {Berlin, Germany},  editor = {Michael N{\"o}lle and Michael Rubik},  url = {http://muscle.prip.tuwien.ac.at/coin_workshop2006_proceedings/reisert.pdf},  urldate = {23-1-2008},  abstract = {This paper presents a coin recognition system based completely on  the direction of the gradient vectors. To optimally align two coins  we search for a rotation such that as most as possible corresponding  gradient vectors point into the same direction. After discretizing  the gradient directions this can be done quickly by the use of the  Fast Fourier Transform. The classification is done by a simple nearest  neighbor search followed by several rejection criteria to meet the  demand of a low false positive rate.},  affiliation = {Albert-Ludwig University Freiburg, Faculty for Applied Sciences, Department  of Compter Science}}Detailed algorithm description can be found in:@UNPUBLISHED{Kotz2007,  author = {Christian Kotz},  title = {Practical Work: Automatic Coin Recognition. LVA-Nr. 183.176},  note = {Pattern Recognition and Image Procesing Group. Institute of Computer  Aided Automation. Faculty of Informatics. Vienna Univerity of Technology.  unpublished.},  month = oct,  year = {2007},  affiliation = {University of Technical Science Vienna, Faculty of Informatics, Department  of Computer Aided Automation, Pattern Recognition and Image Processing Group},  file = {:./CoinReport.pdf:PDF},  keywords = {coins},  owner = {CK},  school = {Pattern Recognition and Image Procesing Group. Institute of Computer  Aided Automation. Faculty of Informatics. Vienna Univerity of Technology},  type = {Practical Work Report}}