Cash Validation And Exchange Using ARM 7
Suraj Panditrao Jogdand, Ankita Harishchandra Kedare, Priyanka Balasaheb Sonawane, Prof.D A Shaikh · International journal of advance research and innovative ideas in education · 2016
“Fake currency detection” is important factor in worldwide. Affects of that scams, Bank Robbery , corn and so many unfair happening.”It is estimated that around 1,69,000 crores of fake rupees are in circulation all over India. Both government and banks are in a denial mode, because probably they do not know what to do.” Fake currency changes from low quality colour scanner based notes to high quality counterfeits whose production is sponsored by unfriendliness. Due to their harmful effect on the economy, detecting fake currency notes is a work of national importance. However, automated approaches for fake currency detection are effective only for low quality fraudalent; manual examination is required to detect high quality fraudalent. Furthermore, no automatic method exists for the more complex – and important – problem of identifying the source of fake notes. This paper describes an efficient automatic framework for detecting fake currency notes. Also, it denotes a classification framework for linking original notes to their source printing presses. Experimental results demonstrate that the detection and classification frameworks have a more number of accuracy. Moreover, the approach can be used to link high quality fraudalent Indian currency notes to their unauthorized sources.