I am astudent of one of the leading colleges in Nagpur, and i have to make a good project,i have taken topic Indian paper currency recognition and verification by using MATLAB coding .I need assistance and also would want to add my own idea in anyway to improve the topic.
Reference:
https://seminarproject.net/Thread-credit...z19X0aD820
PLEASE I NEED INDIAN CURRENCY RECOGNITION USING NEURAL NETWORK
Automatic methods for paper currency recognition become important in many applications such as automated teller
machine and automated goods seller machines. This system is designed to recognize and verify the Indian paper currency.
The approach consists of a number of steps including image acquisition, gray scale conversion, edge detection, feature
extraction, image segmentation and comparison of images [1]. This is a challenging issue to system designers. Every
year RBI (Reserve bank of India) face the counterfeit currency notes or destroyed notes [2]. Handling of large volume of
counterfeit notes imposes additional problems. Therefore, involving machines (independently or as assistance to the
human experts) makes notes recognition process simpler and efficient.
Automatic method for detection of fake currency note is very important in every country. In this approach we extract
the general attributes of the paper currency like identification mark and serial numbers of currency. The identification
marks helps to know the denomination of currency [7]. The serial number of currency helps to detect fake or genuine. The
system is designed to check Indian currency notes of 100, 500 and 1000 rupees. The system will display currency
denomination and either currency is genuine or fake.
With development of modern banking services, automatic
methods for paper currency recognition become important
in many applications such as in automated teller machines
and automatic goods seller machines. The needs for
automatic banknote recognition systems encouraged many
researchers to develop corresponding robust and reliable
techniques. Processing speed and recognition accuracy are
generally two important targets in such systems.
Modernization of the financial system is a milestone in
protecting the economic prosperity, and maintaining social
harmony. Automatic machines capable of recognizing
banknotes are massively used in automatic dispensers of a
number of different products, ranging from cigarettes to bus tickets, as well as in many automatic banking operations.
The needs for automatic banknote recognition systems
encouraged many researchers to develop corresponding
robust and reliable techniques [1-5]. Processing speed and
recognition accuracy are generally two important targets in
such systems. The technology of currency recognition aims
to search and extract the visible and hidden marks on paper
currency for efficient classification. Until now, there are
many methods proposed for paper currency recognition.
The simplest way is to make use of the visible features of
the paper currency, for example, the size and color of the
paper currency [1]. However, this kind of methods has great
limitations as banknotes are getting worn and torn with the
passing of time and they are even dirtier when holding by
dirty hands or in dirt. If any banknote is dirty or it may be
changed into any other color then the color content of
banknote may change largely.