an indian coin recognition matlab code
#1

Hi! Sir, I am Dhivya I do my project coin recognition please be help send mail id : divya.bharu20[at]gmail.om
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#2
It is proposed to introduce the ML-CPNN approach. The characteristics of old coins and new coins of different denominations are considered for classification. Indian coins are released with different values and classified according to different currency parameters such as shape, size, surface, weight and so on. The currencies of some countries have the same parameters, but with a different value. Coins are well recognized by the zoom processes by which the size of a coin in the image is increased. A method is proposed for realizing a more efficient automatic coin recognition system. The Robert edge detection method gives 93% accuracy and the Laplacian method of Gaussion 95% of the result, the Canny edge detection method produces 97.25% result and the ML-CPNN approach yields 99.47 % of the recognition rate. 

Coins are an integral part of our life. Coins are used everywhere, such as in banks, grocery stores, supermarkets, buses, trains, etc. Therefore, there is an obvious need for coins to be automatically recognized and sorted by computers. The machines must be able to recognize the coins correctly since the additional transactions depend on the accuracy of the recognition. Currency recognition systems should be robust in the way they should be able to recognize coin images efficiently, even if there is noise. The Indian currency recognition system recognizes the Indian currencies denominated `1,` 2, `5 and` 10 with rotation invariance and classifies them according to their value. The performance of the Indian currency recognition system is evaluated under noise and noise-free environment. Scanned images of Indian coins have been used as input. After preprocessing, features are extracted from images using Discrete Wavelet Transform (DWT) and neural networks are used for classification. The medium and wiener noise filters are used to improve the image when there is gaussian noise and salt and pepper respectively.

Currency recognition is one of the emerging fields of research in modren times. There is a vital need for an efficient and robust coin recognition system in our daily lives. Coins are an integral part of our life; we can not imagine our daily lives without them. Despite everyday uses, the currency recognition system may prove useful for the purpose of recognition in research organizations dealing with old coins. Therefore, there is an obvious need for coins to be automatically recognized and sorted by computers. The recognition system should be able to correctly recognize the coins, since the additional transactions would depend on the accuracy of the recognition.
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