Image analysis – Applications – Reading paper currency
Reexamination Certificate
1994-04-12
2003-03-25
Tran, Phuoc (Department: 2621)
Image analysis
Applications
Reading paper currency
C382S321000
Reexamination Certificate
active
06539104
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates, in general, to currency identification. The invention relates more particularly to a method and apparatus for automatic discrimination of currency bills of different denominations using light reflectivity characteristics of indicia printed upon the currency bills.
BACKGROUND OF THE INVENTION
A variety of techniques and apparatus have been used to satisfy the requirements of automated currency handling systems. At the lower end of sophistication in this area of technology are systems capable of handling only a specific type of currency, such as a specific dollar denomination, while rejecting all other currency types. At the upper end are complex systems which are capable of identifying and discriminating among multiple currency denominations.
Currency discrimination systems typically employ either magnetic sensing or optical sensing for discriminating between different currency denominations. Magnetic sensing is based on detecting the presence or absence of magnetic ink in portions of the printed indicia on the currency by using magnetic sensors, usually ferrite core-based sensors, and using the detected magnetic signals, after undergoing analog or digital processing, as the basis for currency discrimination. The more commonly used optical sensing technique, on the other hand, is based on detecting and analyzing variations in light reflectance or transmissivity characteristics occurring when a currency bill is illuminated and scanned by a strip of focused light. The subsequent currency discrimination is based on the comparison of sensed optical characteristics with prestored parameters for different currency denominations, while accounting for adequate tolerances reflecting differences among individual bills of a given denomination.
A major obstacle in implementing automated currency discrimination systems is obtaining an optimum compromise between the criteria used to adequately define the characteristic pattern for a particular currency denomination and the time required to analyze test data and compare it to predefined parameters in order to identify the currency bill under scrutiny. Even with the use of microprocessors for processing the test data resulting from the scanning of a bill, a finite amount of time is required for acquiring samples and for the process of comparing the test data to stored parameters to identify the denomination of the bill.
Most of the optical scanning systems available today utilize complex algorithms for obtaining a large number of reflectance data samples as a currency bill is scanned by an optical scanhead and for subsequently comparing the data to corresponding stored parameters to identify the bill denomination. Conventional systems require a relatively large number of optical samples per bill scan in order to sufficiently discriminate between currency denominations, particularly those denominations for which the reflectance patterns are not markedly distinguishable. The use of the large number of data samples slows down the rate at which incoming bills may be scanned and, more importantly, requires a correspondingly longer period of time to process the data in accordance with the discrimination algorithm.
The end result is that systems capable of accurate currency discrimination are costly and generally incapable of currency discrimination at high speeds with a high degree of accuracy.
SUMMARY OF THE INVENTION
It is a principal object of the present invention to provide an improved method and apparatus for identifying currency bills comprising a plurality of currency denominations.
It is another object of this invention to provide an improved method and apparatus of the above kind which is capable of efficiently discriminating among bills of several currency denominations at a high speed and with a high degree of accuracy.
A related object of the present invention is to provide such an improved currency discrimination apparatus which is compact, economical, and has uncomplicated construction and operation.
Briefly, in accordance with the present invention, the objectives enumerated above are achieved by means of an improved optical sensing and correlation technique adopted to both counting and denomination discrimination of currency bills. The technique is based on the optical sensing of bill reflectance characteristics obtained by illuminating and scanning a bill along one of its dimensions (wide or narrow), approximately about the central section of the bill. Light reflected from the bill as it is optically scanned is detected and used as an analog representation of the variation in the dark and light content of the printed pattern or indicia on the bill surface.
A series of such detected reflectance signals are obtained by sampling and digitally processing, under microprocessor control, the reflected light at a plurality of predefined sample points as the bill is moved across the illuminated strip with the preselected dimension along which the bill is scanned being maintained parallel to the direction of transport of the bill. Accordingly, a fixed number of reflectance samples is obtained across the preselected dimension of the note. The data samples obtained for a bill scan are subjected to digital processing, including a normalizing process to deaccentuate variations due to “contrast” fluctuations in the printed pattern or indicia existing on the surface of the bill being scanned. The normalized reflectance data represent a characteristic pattern that is fairly unique for a given bill denomination and incorporates sufficient distinguishing features between characteristic patterns for different currency denominations so as to accurately differentiate therebetween.
By using the above approach, a series of master characteristic patterns are generated and stored using standard bills for each denomination of currency that is to be detected. The “standard” bills used to generate the master characteristic patterns are preferably bills that are slightly used bills. According to a preferred embodiment, two characteristic patterns are generated and stored within system memory for each detectable currency denomination. The stored patterns correspond, respectively, to optical scans performed on the green surface of a bill along “forward” and “reverse” directions relative to the pattern printed on the bill. For bills which produce significant pattern changes when shifted slightly to the left or right, such as the $10 bill in U.S. currency, it is preferred to store two patterns for each of the “forward” and “reverse directions, each pair of patterns for the same direction represent two scan areas that are slightly displaced from each other along the non-preselected dimension of the bill. Preferably, the currency discrimination and counting method and apparatus of this invention is adapted to identify seven (7) different denominations of U.S. currency, i.e., $1, $2, $5, $10, $20, $50 and $100. Accordingly, a master set of 16 different characteristic patterns is stored within the system memory for subsequent correlation purposes (four patterns for the $10 bill and two patterns for each of the other denominations.
According to the correlation technique of this invention, the pattern generated by scanning a bill under test and processing the sampled data is compared with each of the 16 prestored characteristic patterns to generate, for each comparison, a correlation number representing the extent of similarity between corresponding ones of the plurality of data samples for the compared patterns. Denomination identification is based on designating the scanned bill as belonging to the denomination corresponding to the stored characteristic pattern for which the correlation number resulting from pattern comparison is determined to be the highest. The possibility of a scanned bill having its denomination mischaracterized following the comparison of characteristic patterns, is significantly reduced by defining a bi-level threshold of correlation that must be satisfied for a “positive” call to be made.
In
Bauch Aaron M.
Graves Bradford T.
Raterman Donald P.
Stromme Lars R.
Cummins-Allison Corp.
Jenkens & Gilchrist
Tran Phuoc
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