Showing papers by "Kamil Dimililer published in 2005"

Comparison Criteria for Optimum Image Compression

Abstract: Recently, many efficient image compression methods have been developed in order to compress image data prior to further processing. Discrete cosine transforms and wavelet transforms are examples of these compression methods. The aim of the work presented within this paper is to introduce comparison criteria for optimum compression using these well known image compression techniques. The comparison criteria will comprise visual inspection and computed analysis

Deformed banknote identification using pattern averaging and neural networks

Abstract: Neural networks combined with image processing can provide sufficient solutions to problems where automation and machine intelligence is required. An Intelligent Banknote Identification System that is able to recognise clean and deformed banknotes may be used to aid identification by machines or banknote counters. For such as system to be useful in real-life applications it must be also be fast, efficient and simple to use. This paper presents a fast intelligent banknote identification system that is able to recognise clean and deformed banknotes. Banknote image compression using Discrete Cosine Transform (DCT) and Biorthogonal Wavelet Transform (BWT) is used to simulate four levels of banknote deformation. The deformed banknotes will be used to test the trained neural network. A real-life application will be presented where this system is used to identify EURO banknotes and the new Turkish Lira (TL) banknotes. Experimental results suggest that the developed system perfoms well when using highly deformed banknote images as well as clean images; thus providing a fast, efficient system for recognizing banknotes.