CLAIMS

1. A method of recognizing a denomination of paper money, comprising:

receiving an image of the paper money comprising figures and letters in order to extract an image of a specific portion which characterizes the denomination;

allocating an image of the specific portion to an area having a predetermined number of pixels, converting values of quantitated pixels into numerical values, and arranging the numerical values in a sequence to generate input data;

inputting the input data into a neural network which has learnt a plurality of pieces of standard data corresponding to various denominations of paper money to allow the input data to be compared with the plurality of pieces of standard data and outputting probability values corresponding to a number of cases of each denomination; and

arranging the probability values output from the neural network in a descending order, selecting a case corresponding to standard data having the highest probability value, and outputting a denomination corresponding to the selected case as recognition data.

2. The method of claim 1 , further comprising determining whether an error is present in the recognizing of a denomination of paper money by using the highest and second highest probability values of the probability values and outputting error detection data in order to determine a validity of a recognition of a denomination.

3. The method of claim 2, wherein if the first probability value is less than or greater than a predetermined reference value and a difference between the first probability value and the second probability value is within a predetermined range, it is determined that the error is present.

4. The method of claim 1 , wherein the plurality of pieces of standard data are obtained through combinations of upper/left and lower/right portions of front and back surfaces of each denomination of paper money.

5. The method of claim 1 , wherein an image of the specific portion is divided into a plurality of blocks having predetermined sizes, pixel values of the blocks are averaged, and input data is generated using average values of the blocks.

6. The method of claim 1 , wherein the receiving of an image of paper money comprising figures and letters in order to extract an image of a specific portion which characterizes the denomination comprises:

obtaining the image of the paper money;

extracting an outline of the paper money of the obtained image; and

extracting an area in a predetermined position as an image of the specific portion based on a center of the image.

7. An apparatus for recognizing a denomination of paper money,

comprising:

a preprocessor receiving an image of paper money comprising figures and letters, extracting an image of a portion characterizing the denomination, allocating the image to an area having a predetermined number of pixels, converting values of quantitated pixels of the area into numerical values, and arranging the numerical values in a sequence to generate input data;

a function processor inputting the input data into a neural network which has learnt a plurality of pieces of standard data corresponding to various denominations of the paper money to allow the input data to be compared with the plurality of pieces of standard data, outputting probability values depending on a number of cases

corresponding to each denomination, arranging the probability values in a descending order, selecting a case corresponding to standard data having the highest probability value, and outputting a denomination corresponding to the case as recognition data; and

a storage storing the input data and the standard data preprocessed by the preprocessor.

8. The apparatus of claim 7, further comprising an error detector

determining whether an error is present by using the highest and second highest probability values of the probability values output from the function processor and outputting error detection data in order to determine a validity of a recognition of the denomination of paper money.

9. The apparatus of claim 8, if the first probability value is less than or greater than a predetermined reference value and a difference between the first probability value and the second probability value is within a predetermined range, the error detector determines that an error is present.

10. A denomination recognizing paper money counter comprising an inlet into which paper money is put, a counter counting the number of pieces of paper money, an outlet discharging the paper money, and a display displaying information regarding the counted paper money, comprising:

a scanner scanning an image of the paper money put through the inlet;

a preprocessor receiving the image of the paper money through the scanner, extracting an image of a portion characterizing a denomination, allocating the image of the portion characterizing the denomination to an area having a predetermined number of pixels, converting values of quantitated pixels of the area into numerical values, and arranging the numerical values in a sequence to generate input data;

a function processor inputting the input data into a neural network which has learnt a plurality of pieces of standard data corresponding to various denominations of paper money to allow the input data to be compared with the plurality of pieces of standard data, outputting probability values depending on a number of cases of each of the denominations, arranging the probability values in a descending order, selecting a case corresponding to standard data having the highest probability value, and

outputting a denomination corresponding to the case as recognition data; and

a storage storing the input data and the plurality of pieces of standard data preprocessed by the preprocessor.

11. A computer-readable recording medium having embodied thereon a computer program for implementing the method of claim 1.