1. Field of the Invention
The present invention relates to image processing, more particularly, a method for detecting a boundary of a monetary banknote within an image.
2. Description of the Prior Art
Advancements in image processing systems, including digital color copiers, scanners, and small scale printing presses, has also lead to reproduction of monetary banknotes, currencies, stocks, bonds, and other irreproducible documents by counterfeiters. Obviously illegal, criminals participate in such activities for personal gain or profit.
Because of the presence of such counterfeit and copied items, there is a need to be able to effectively discern and distinguish such fake items from valid and authentic ones. This task however, becomes increasingly difficult as printing and reproduction advancements allow counterfeiters to reproduce copies that are virtually indistinguishable to the human eye.
One aspect of counterfeit currency detection involves identifying a boundary of a monetary banknote.
Additionally, if the banknote is scanned while embedded in a complicated image background, it may be more difficult to distinguish the actual note from the image background. The image background may also provide additional noise and/or patterns to complicate the detection process and introduce irregularities and errors. Also, variations in the shift, rotation and alignment of the banknote may complicate identification processes. Therefore in these conditions, identification of the banknote boundary is crucial to avoid errors in counterfeit detection.
One objective of the claimed invention is therefore to provide a method for detecting a boundary of a monetary banknote within an image, to solve the above-mentioned problems.
According to an exemplary embodiment of the claimed invention, a method for detecting a boundary of a monetary banknote within an image is disclosed. The method comprises: dividing the image into a plurality of sections; generating a color feature map containing color histogram data for each section of the image; generating a gray level feature map indicating a gray level value for each section of the image; recording border sections onto a banknote boundary map, the border sections being sections having color histogram data within a first predetermined range and gray levels within a second predetermined range; removing internal border sections enclosed by perimeter border sections from the banknote boundary map; and dilating the perimeter border sections on the banknote boundary map.
These and other objectives of the present invention will no doubt become obvious to those of ordinary skill in the art after reading the following detailed description of the preferred embodiment that is illustrated in the various figures and drawings.
In order to aid in the detection and verification of monetary banknotes, the present invention provides a method for detecting a boundary of a monetary banknote within an image. The method can be applied for use in the detection of counterfeit currency. An image, containing a scan of the banknote, can be provided with an arbitrary rotational axis and shift alignment for banknote boundary detection. Additionally, the image can contain the monetary banknote while superimposed onto an arbitrary background, can include multiple isolated and independent banknotes, or have overlapping banknotes within the image. The method can be used in conjunction with basic stand-alone scanners, copiers, stand-alone printers, and other related detection and scanning hardware.
Detection of a banknote boundary will allow for the separation of multiple banknotes when on the same image scan. This will also help distinguish multiple banknotes if they are found overlapping. Once the banknote boundary is detected, banknote verification techniques can be applied to the banknote main body, as it typically contains more distinguishing features which can be used in banknote verification processes.
An overview of the method for detecting a boundary of a monetary banknote within an image is provided with reference to
Although a general process overview is already provided above, further detail of each relevant section is provided below.
During image division 210, the received image is divided into a plurality of sections.
Color feature map generation 220 entails generating a color feature map containing color histogram data for each section of the image. An example of color histogram data is provided in
The color feature map, as shown in
In gray level texture feature map generation 240, a gray level texture feature map is created that indicates a gray level value for each section of the image. An exemplary illustration is shown in
Banknote boundary map generation 250 is a pivotal step in which border sections are determined from data in the previous steps, primarily the color feature map, and the gray level texture feature map. In this step, sections having color histogram data within a first predetermined range, and also having gray level values within a second predetermined range, are identified as border sections and recorded onto the banknote boundary map. The first predetermined range is based on color histogram data for a border of a valid monetary banknote, while the second predetermined range is based on gray levels for a border of a valid monetary banknote. Therefore, as the predetermined ranges above are specifically tuned and chosen according to border information of a valid banknote, this step appropriately selects border sections using the correct criteria. This step is further illustrated in
Note from
With border sections identified, the next step comprises banknote main body block removal 260. Note from
Removal of the internal border sections enclosed by perimeter border sections can be conducted according to a number of criteria. In a preferred embodiment, the method can remove a number of internal border sections according to number of sections being greater than a threshold number. Additional embodiments may utilize removing internal border sections in the banknote boundary map such that the removed internal border sections correspond to a predetermined surface area.
The final step in the boundary detection method of the present invention involves banknote boundary dilation. This step is illustrated in
A method for detecting a boundary of a monetary banknote within an image according to an exemplary embodiment of the present invention is additionally described in the process flow chart of
Step 910: Divide the image into a plurality of sections as shown in
Step 920: Generate a color feature map as shown in
Step 940: Generate a gray level feature map as illustrated in
Step 950: Record border sections onto a banknote boundary map such as shown in
Step 960: Remove internal border sections enclosed by perimeter border sections from the banknote boundary map as illustrated in
Step 970: Dilate the perimeter border sections on the banknote boundary map as illustrated in
By detecting a boundary of a monetary banknote within an image, the present invention provides a method to aid in the detection of counterfeit banknotes and currencies. Once the banknote boundary is detected, banknote verification techniques can be applied to the banknote main body. The banknote main body generally contains more distinguishing features which can therefore be identified for additional banknote verification processes.
Detection of a banknote boundary will also allow for the separation of multiple banknotes when on the same image scan. This will also help distinguish multiple banknotes if they are found overlapping or even on a complicated background.
Those skilled in the art will readily observe that numerous modifications and alterations of the device and method may be made while retaining the teachings of the invention. Accordingly, the above disclosure should be construed as limited only by the metes and bounds of the appended claims.
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