Abstract

Use of the coins has been started in Asia Minor during 7th century B. C. Dates back between 2500 B. C and 1700 B. C. Coins were used to trade in the Indus valley of Mohenjo-Daro and Harappa. Ancient coins are always tough to identify and recognize. Weathering and other natural causes degrades it overall structure. Classification of such ancient coins using computer vision and machine intelligence is a challenging task. Here in this paper this task has been taken to be addressed. This paper aims to develop a intelligent system which can classify and recognize ancient coins through their images only. The approach involves feature extraction classification and recognition. Standard deviation of the histogram of the image has been considered as a feature which is then classified and recognized by feed forward back propagation artificial neural network. Preprocessing of the image includes filtering of the image for better results.

References

• Sebastian Zambanini and Martin Kampel, " Segmentation of Ancient Coins Based on Local Entropy and Gray Value Range",Computer Vision Winter Workshop 2008,Janez Per?s(ed. ).
• X. Munoz, J. Freixenet, X. Cufi, J. Marti," Strategies for image segmentation combining region and boundary information, Pattern Recognition Letters 24(2003).
• Fritz Albregtsen," Region & Edge Based Segmentation of INF4300-Digital Image Analysis",page no 5-53.
• Sebastian Zambanini-Martin Kampel," Coin Data Acquisition for Image Rcognition".
• Shatrughan Modi and Dr. Seema Bawa," Automated Coin Recognition System using ANN", International Journal of Computer Applications (0975-8887) Volume 26-No. 4,July 2011.
• Maia Zaharieva, Martin Kampel and Sebastian Zambanini. " Image based recognition of coins-An overview of the COINS project.
• Muhammad Naveed, Rehanullah Khan, Zeeshan Khan, Syed Qasim Sattar, Yasir Ali Shah," Coins Detection Using Eigen Faces Based Upon Principal Component Analysis".
• Reinhold Huber-Mörk, Sebastian Zambanini, Maia Zaharieva,Martin Kampel," Identification of ancient coins based on fusion of shape and local features". Received:4August 2009/Revised:23April 2010/Accepted:20 June 2010/Published online:11July 2012.
• Cezar Popescu,"A Recursive Approach to Identify the Objects in a 2D Image".
• Bradford Bonney, Robert Ives, Delores Etter, Yingzi Du, "IRIS Pattern Extraction Using Bot Planes and Standard Deviations".
• Sabyasachi Dey, Bhargab B. Bhattacharya, Malay K. Kundu, Tinku Acharya, "A Simple Architecture for Computing Moments and Orientation of an Image". Fundamenta Informaticae 52 (2002) 1-11 IOS Press.
• Hsien-Chu Wu, Chwei-Shyong Tsai, Ching-Hao Lai, "A Licence Plate Recognition System in E-Government".
• C. -C. Yang, S. O. Prasher, J. -A. Landry, H. S. Ramaswamy and A. Ditommaso, "Application of artificial neural networks in image recognition and classification of crop and weeds".
• Komal Vij, Yaduvir Singh, "Enhancement of Images Using Histogram Processing Techniques".
• Amit Kumar Gupta and Yash Pal Singh, "Analysis of Back Propagation of Neural Network Method in the String Recognition".
• Networks for Pattern Recognition,Cambridge,TheMITPress,1993
• Torsten Seemann, "Digital Image Processing Using Local Segmentation"
• C. M. Velu and P. Vivekanandan, "Indian Coin Recognition System of Image Segmentation by Heuristic Approach and Houch Transform (HT)"
• Velu C M, P. Vivekanadan, Kashwan K R, "Indian Coin Recognition and Sum Counting System of Image Data Mining Using Artificial Neural Networks".