TY - JOUR ID - TI - Multiple Segmentation Methods for Iraqi Paper Currency (IPC) AU - Shaimaa Hameed Shaker شيماء حيد شاكر AU - Mohammed Gheni Alwan محمد غني PY - 2019 VL - 11 th year IS - 1 SP - 159 EP - 170 JO - AL-yarmouk Journal مجلة اليرموك SN - 20752954 AB - The segmentation of images is a vital topic in the field of image processing. It depends on a series of subsequent operations and process. The subsequent processes in this research reviewed three methods of segmentation: Adaptive thresholding, Fuzzy C mean, and k-mean for currency image segmentation. The three methods applied on the IPC and the results in subsequent operations can be important in the extract features that will be useful in different approach such counterfeit currency. The three methods were applied to the paper currency (PC) images with a dependence on two layers (K =2) and the value of the number of layers was increased with Fuzzy C-mean and K-mean segmentation Such as five layers, for example. A convergence of the results of the three methods was observed and it can be used in the case of two layers with a better Adaptive thresholding segmentation. If you choose more than two layers, we notice a Fuzzy C mean that gives better results.

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