DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim(s) 15 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claim 15, last two lines, the phrase “and/or by form a sliding average from the error pixels contained in the error images” is unclear and indefinite.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 12-14 and 16-22 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hecht et al (US 2013/0311477 A1).
Regarding Claim 12, Hecht discloses
an apparatus for checking value documents, i.e., banknote processing apparatus (10), as illustrated in figure 1, and more particularly
banknotes, as mentioned at paragraph 1, having at least one image-capturing device, i.e., sensor unit (26) with optical unit (28), as illustrated in figure 1, which is designed to capture at least one image of each of a plurality of value documents, as mentioned at paragraph 38, said images each being
composed of a plurality of pixels, as mentioned at paragraph 4,
wherein an evaluation device, which is designed to determine, in the captured images of different value documents, one or more positions of pixels at which a plurality of the
captured images of the different value documents deviate from a predefined reference
image, as mentioned at paragraphs 38 and 39, which states as follows.
[0038] For the creation of a digital image of a bank note 12 upon the transport of the bank note 12 through the field of view of the sensor unit 26, the sensor unit 26 can be configured such that an image is captured simultaneously for the entire bank note 12. It is also possible, however, that a sensor line of the sensor unit 26 captures line by line image data of a bank note 12 moved past the sensor line and the image data thus captured are assembled into a digital image of the bank note 12. The image data for a pixel comprise the pixel value or in the case of colored images the pixel values or color coordinate values (for example in the CIE XYZ color space), as well as the place or the location of the pixel on the bank note. A suitable color detection device, which can be employed as a sensor unit 26 in the bank note processing apparatus 10 according to the invention is described for example in WO 2006/018283.
[0039] In the case of colored images, pixel values or color coordinate values can be generated in an arbitrary manner. For example, digital images of bank notes can be captured simultaneously or one after the other in several spectral regions specified preferably in dependence on the employed color space. The color coordinate values can here be obtained either directly by employing suitable sensor or detection units or after transformation of other captured image data.
Emphasis provided.
Regarding Claim 13, Hecht discloses
wherein the evaluation device (28) is
designed to:
determine, from the captured images of different value documents (312), in each case an error image, i.e., detected images as mentioned in paragraph 21, which contains one or more error pixels, at the positions of which the captured image of the respective value document deviates from the reference image, i.e., noting the mention of detection of errors in alignment of reference images in paragraph 21, and
determine from the error images a repetition error image that contains one or more deviation pixels whose positions correspond to the positions of error pixels at which a plurality of the captured images of the different value documents deviate from the reference image, as mentioned in paragraphs 21, 59 and 60, which state as follows.
[0021] In accordance with a further preferred embodiment, the pixel values of a respective pixel of the class reference image are determined by the difference between the maximum pixel value and the minimum pixel value of the corresponding pixels of the plurality of reference images of already classified value documents of the same class. This is particularly advantageous insofar as there can thus be detected errors in the alignment of the reference images of the already classified value documents of the same class upon the creation of the class reference image. This can be done either by a user by means of the graphical user interface, which displays the class reference image, and/or automatically by a corresponding algorithm implemented for example as a software. If for example the intensity in an extended pixel region of the class reference image created in this way exceeds a predetermined threshold value, this may be due to an error in the alignment of the images of the already classified value documents of the same class. In such a case, the method according to the invention provides that the class reference data record created with the faulty alignment is discarded and a new class reference data record is created with a corrected alignment.
[0059] In a further preferred embodiment, the pixel values of a pixel of the class reference image are the average values of the corresponding pixel values of the corresponding pixels of the plurality of reference images of already classified value documents of the same class. For this purpose, the pixel value of a pixel of the class reference image, which pixel is arranged at the position x, y, is allocated the averaged value of the pixel values of the pixels of the plurality of reference images at the position x, y (where applicable, after an alignment with a common reference point by means of the above-described alignment mechanism). This is advantageous upon the definition of a region in which upon the subsequent classification of bank notes a security feature, e.g. the security thread 340 of the bank note 312 of FIG. 4, is to be found with high probability.
[0060] In accordance with a further preferred embodiment, the pixel values of a respective pixel of the class reference image are determined by the difference between the maximum pixel value and the minimum pixel value of the corresponding pixels of the plurality of reference images of already classified value documents of the same class. For this purpose, the pixel value of a pixel of the class reference image, which pixel is arranged at the position x, y is allocated the difference between the maximum and the minimum value of the pixel values of the pixels of the plurality of reference images at the position x, y (where applicable, after an alignment with a common reference point by means of the above-described alignment mechanism). This is particularly advantageous insofar as there can be detected errors in the alignment of the reference images of the already classified bank notes of the same class upon the creation of the class reference image. This can be done either by a user by means of the graphical user interface, which displays the class reference image, and/or automatically by an accordingly configured software routine. If for example the intensity in an extended pixel region of the class reference image created in this way exceeds a predetermined threshold value, this may be due to an error in the alignment of the reference images of the already classified bank notes of the same class. Because with a class reference image thus created, pixels that in a reference image are part of the bright margin region of a reference bank note and in another reference image are part of the dark background outside a reference bank note have a high intensity. In such a case, the alignment algorithm is corrected and/or a new set of reference images for each class is created.
Emphasis provided.
Regarding Claim 14, Hecht discloses
wherein the evaluation device is
designed to determine in each case a deviation pixel value for the deviation pixels taking into account a frequency with which the corresponding positions of error pixels are contained in the error images, as mentioned at paragraphs 21, 59 and 60, for example.
Regarding Claim 16, Hecht discloses
wherein the evaluation device is designed to determine a current repetition error image from a current error image and a previous repetition error image,
wherein the current error image is determined from the currently captured image of a
value document, and the previous repetition error image was determined from error images which were captured from images of value documents which were captured before the currently captured image, noting that the error images captured by Hecht’s imaging system of banknotes includes prior and current images that are interpreted as a current banknote image, class reference parameters of a class reference data record, as mentioned at paragraphs 8, 13 and 53, for example, which state as follows.
[0008] The method according to the invention for determining a class reference data record for the classification of value documents, in particular bank notes, has the following steps: the creating of a class reference image by means of a plurality of reference images of already classified value documents of the same class, i.e. by means of a plurality of images of reference value documents of a class; and the creating of the class reference data record having at least one class reference parameter with the aid of the class reference image. Here, the solution according to the invention is characterized in that the pixel values or intensity values of a respective pixel of the class reference image are a function of the pixel values of the corresponding pixels of the plurality of reference images of already classified value documents of the same class.
[0013] Since in the case of a large number of security features and classification criteria of a value document, the specialist knowledge and the experience of experts are often required to guarantee a reliable specification and setting of the class reference parameters of a class reference data record, it has proven to be advantageous that, during the adaptation process, the class reference image of a class of value documents is represented, for the analysis, on a display unit by means of a graphical user interface. Advantageously, the graphical user interface allows the user to participate in the creation of class reference parameters of a class reference data record with the aid of the class reference image, for example by the user defining particular regions of the class reference image by means of the graphical user interface and the regions thus defined being used for creating or adjusting class reference parameters of a class reference data record. Likewise, the creation of the class reference parameters of a class reference data record with the aid of the class reference image can be effected at least partly or completely without the participation of a user, for example by means of suitable software routines that are configured to determine regions of particular pixel values in a digital image.
[0053] As this can be inferred from FIG. 1, the control and evaluation unit 30 of the bank note processing apparatus 10 is connected preferably with a computer 38 that has a display unit 39. On the computer 38 there is preferably implemented a graphical user interface, by means of which for example the above-described class reference image based on the minima of the pixel values of the reference images can be represented on the display unit 39, so that a user can analyze the class reference image and, where applicable, can act on the creation or adjustment of a class reference data record. Preferably, the graphical user interface is configured such that a user, by means of the graphical user interface, can define regions of the class reference image, which lead to the creation or adjustment of the class reference data record. For example, a user can define, by means of the graphical user interface, the rectangular regions 322 and 332 represented in FIG. 4, in which with high probability the denomination or the serial number of a bank note to be classified of this class is to be found. Preferably, these regions can be defined by means of functions known to the person skilled in the art from drawing programs, such as for example the function that moving a computer mouse with the mouse button pressed leads to an enlargement or reduction in size of the rectangular region. Of course, regions with different regular and irregular shapes, such as for example circular, elliptical, triangular, and the like, are also thinkable. An enlargement or reduction in size of the regions 322 and/or 332 by the user by means of the graphical user interface preferably leads to the fact that the respective tolerance ranges of the class reference parameters assigned to the denomination and/or the serial number are accordingly enlarged or reduced in size. This makes it possible to adjust the class reference parameter of a class reference data record and its tolerance range in such a way that the denominations and/or serial numbers of the bank notes to be classified of this class lie with high probability within this tolerance range thus determined. However, it is also conceivable that these regions are determined by a software routine implemented on the computer 38 and/or the control and evaluation unit 30, which software routine allows to ascertain regions of a certain intensity in the class reference image, and therefore the creation of a class reference data record can be effected without an action of a user. The computer 38 can further be connected with an external database 40 for storing large amounts of data, in particular image data. In other embodiments it is also conceivable that the computer 38 and/or the external database 40 are part of the control and evaluation device 30.
Emphasis provided.
Regarding Claim 17, Hecht discloses
having a user interface, i.e, display (39) as illustrated in figure 1 and as mentioned at paragraph 53, for example, which is designed to reproduce the determined positions of the pixels at which a plurality of the captured images of the different value documents (312) deviate from the predefined reference image, or the at least one repetition error image, as illustrated in figures 3a and 3b and as mentioned at paragraphs 21, 28, 53 and 60 and Claims 20 and 30, for example.
Regarding Claim 18, Hecht discloses
having a control device, i.e., a processor as mentioned at paragraph 25, computer (38) and a control and evaluation device (30) as mentioned at paragraphs 36 and 53 and as illustrated in figure 1, which is designed to control processing, and more particularly sorting, of the value documents (12) as a function of the determined positions of the pixels at which a plurality of the captured images of the different value documents (12) deviate from a predefined reference image or as a function of the at least one repetition error image, noting paragraphs 34, 36 and 44 also mentions gate device (20) and other gate devices which sort the banknotes into output pockets (22a-c) and 24, for example.
Regarding Claim 19, Hecht discloses
a system for processing value documents (10), and more particularly
banknotes (12), having at least one apparatus for processing, and more particularly separating, via singulation device (16), conveying, i.e, via transporter (18), and/or sorting, i.e., via gates (20), value documents (12) and at least one apparatus (26, 28, 30, 32, 34, 36, 38, 39, 40) for checking value documents according to claim 12.
Regarding Claim 20, see the rejection of Claim 12, above.
Regarding Claim 21, Hecht discloses
a computer program product (36) comprising commands, i.e., code, which, when the program is executed by a computer (30, 32), cause the computer to carry out the method according to claim 20, as mentioned at paragraph 42 and as illustrated in figure 1, for example.
Regarding Claim 22, Hecht discloses
a computer-readable storage medium (36) comprising commands, i.e. code, which, when executed by a computer (30, 32), cause the computer to carry out the method according to claim 20, as mentioned at paragraph 42 and as illustrated in figure 1, for example.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hecht et al (US 2013/0311477 A1) in view of Zaklika et al (US 2005/0180659 A1).
Regarding Claim 15, Hecht teaches the system as described above.
Regarding Claim 15, Hecht does not expressly teach
wherein the evaluation device is designed to determine in each case a deviation pixel value for the deviation pixels by means of exponential smoothing and/or by form a sliding average from the error pixels contained in the error images.
Regarding Claim 15, Hecht does not expressly teach, but Zaklika teaches
wherein the evaluation device is designed to determine in each case a deviation pixel value for the deviation pixels by means of exponential smoothing and/or by form a sliding average from the error pixels contained in the error images, as mentioned at paragraphs 142-147 as follows.
[0142] Other methods of determining an optimal sampling region size that is adaptive to image content are also contemplated. As discussed, the statistical analysis need not be confined simply to the entire sampling region. Instead the statistics inside the sampling region may be compared to those within a region of growth around the original or previous sampling region. This adaptation procedure may also be iterative, wherein the previous sampling region and incremental modification region are combined prior to modifying the sampling region in the next iteration. In some cases, analysis of the incremental modification region may facilitate detection of an abrupt change by limiting the change analysis to incremental portions of the image.
[0143] Other statistical measures than standard deviation may be used. For example, the trend in a uniformity measure, such as color difference variance divided by mean color difference, may be used. Alternatively, the color distribution or smoothed distribution within the tool impression may be analyzed in more detail, such as by use of a histogram, including differential and integral histograms. The distribution may also be represented by means of mixture models.
[0144] More generally, classifiers of various types or clustering methods may be used to characterize the content under the tool impression. In the case of a brush tool, where individual impressions within a stroke may be updated as they are applied, it is preferred to use simple analysis methods for speed and responsiveness of the tool. However, more complex methods may also be used, for example, when the result of processing is drawn upon completion of the stroke and not during the stroke. In various implementations, it may also be sufficient for the adaptive sampling region methods to provide merely a sampling region that is improved over the original sampling region (e.g., an improved sampling region that is more characteristic of the background region intended by the user).
[0145] As previously discussed, it should be understood that the image properties being analyzed and edited are not limited to color. They may include other properties, such as transparency, or they may include explicit feature vectors that characterize, for instance, texture or another spatial property.
[0146] It should also be understood that the method of determining edit classes under the tool impression may be chosen independently of the criteria used to determine an improved size of a sample region. For example, the threshold for erasure may be chosen according to standard deviation of color differences as opposed to color range within the sample, while the sampling region size may be determined using a uniformity metric.
[0147] FIG. 16 illustrates a different exemplary sampling trend 1600 in an adaptive sampling region application. By evaluating a uniformity metric (e.g., color difference variance/mean color difference) in the sampling region as the sampling region grows, an abrupt change in the sampling trend 1600 may be detected at a side length of 114 pixels. In one implementation, the abrupt change can be detected by comparing the uniformity metric difference between two adjacent or predetermined sampling region sizes to a given sampling trend criterion (a specific type of sampling criterion pertaining to trend analyses). In another implementation, an abrupt change in the character of the pixel property distribution may be detected by comparing a metric characterizing the property distribution with a predicted value of that metric obtained, for example, by exponential smoothing or a moving average of prior sampling property distribution metrics.
Emphasis provided.
Regarding Claim 15, before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have provided wherein the evaluation device is designed to determine in each case a deviation pixel value for the deviation pixels by means of exponential smoothing and/or by form a sliding average from the error pixels contained in the error images, as taught by Zak, in the imaging system of Hecht’s apparatus for checking documents so as to elicit features of the pixels of banknote images using typical sampling techniques.
Conclusion
Applicant is encouraged to contact the Examiner should there be any questions about this rejection or in an endeavor to explore potential amendments or potential allowable subject matter.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Adachi ‘211 is cited as using reference marks and pixel data with address position, as mentioned at paragraphs 73-76, 80 and 92-100 and as illustrated in figures 4-11, for example.
Su ‘829 is cited as teaching a banknote sorting apparatus (10) that images banknotes (12) via imaging sensor (32) and processor (34) as illustrated in figures 1-12, for example.
Hatton ‘197 is cited as teaching a system for processing a distorted image using authentication templates to detect non-linear distortion in an image and that uses spatial coordinates in a distortion free image to a set of pixel coordinates, as mentioned at abstract, paragraphs 17 and 29-36, and as illustrated in figures 1-8.
Csulits ‘234 is cited as teaching an imaging system for banknotes using document/banknote scanner/sorter (100) as illustrated in figure 1, and which determines a pixel’s location as mentioned at paragraph 175, for example.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JEFFREY ALAN SHAPIRO whose telephone number is (571)272-6943. The examiner can normally be reached Monday-Friday generally between 8:30AM and 6:30PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anita Y Coupe can be reached at 571-270-3614. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JEFFREY A SHAPIRO/Primary Examiner, Art Unit 3619
June 13, 2026
Prosecution Insights