Approaches in Pattern Recognition and Classification Based on Coin Images

Abstract:

This paper discusses the various texture-based and vector-based approaches to classify coins.These two types of approaches are common for software-based coin sorting systems. Many researchers have applied algorithms known in artificial intelligence research for feature extraction, selection and classification of coin images. However, without a common benchmark, it is difficult to assess the accuracy, robustness and efficiency of the coin sorting systems across the different approaches. It is proposed that the use of a standard benchmark image databank such as the CIS Benchmark will allow a more objective and accurate comparison of the performance of these coin classification approaches.

• Periodical: Applied Mechanics and Materials (Volumes 548-549)
• Pages: 1148-1151
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.548-549.1148
• Online since: April 2014
• Authors: Chee Kong Wong*, Mohd Afizi bin Mohd Shukran, Fong Yee Lee
• Keywords: Coin Classification, Coin Sorting, Content-Based Image Retrieval (CBIR), Image Classification, Image Segmentation, Pattern Recognition

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