FINAL REJECTION
Examiner’s Remarks
Regarding the amendment filed 5/4/2026:
The amendments to claims 2, 14 and 20 are acknowledged and accepted.
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 .
Terminal Disclaimer
The terminal disclaimer filed on 5/4/2026 disclaiming the terminal portion of any patent granted on this application which would extend beyond the expiration date of U.S. Patent Number 11881088 has been reviewed and is accepted. The terminal disclaimer has been recorded.
Claim Objections
Claim 20 is objected to because of the following informalities:
Claim 20 recites “with presence of the foreign object”. Suggested language is “with a presence of the foreign object”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 2-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 2 recites “comparing feature amounts extracted from the images against model features associated with known objects to identify unexpected objects in the one or more hands”, and Claims 14 and 20 recite “analyzing includes comparing feature amounts extracted from the images against model features associated with known objects to identify a foreign object”. The specification does not use the term “feature amounts”, therefore the specification does not appear to describe “feature amounts”. As such, this is considered new matter.
Claims not specifically addressed fail to comply with the written description requirement due to their dependency.
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.
Claims 2-20 are 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.
With respect to claim 2 recites “comparing feature amounts extracted from the images against model features associated with known objects to identify unexpected objects in the one or more hands”. Claims 14 and 20 recite “analyzing includes comparing feature amounts extracted from the images against model features associated with known objects to identify a foreign object”. It is not clear what the applicant means by “feature amounts”. There is no way to determine the metes and bounds of this limitation, especially since the specification does not describe “feature amounts”. Please clarify. For examination purposes, the claim language will be interpreted as features “comparing features extracted from the images against model features associated with known objects to identify unexpected objects in the one or more hands” and “analyzing includes comparing features extracted from the images against model features associated with known objects to identify a foreign object”, respectively.
Claim 2 recites “detecting hand gestures by analyzing the actions to identify potential fraudulent behavior when a hand gesture indicates potential fraudulent behavior along with an unexpected object”. This wording is awkward and confusing since the “detecting hand gestures by analyzing actions…when a hand gesture indicates…” (detecting hand gestures when a hand gesture indicates appears circular). It is not clear if the applicant means that only when a hand gesture indicates potential fraudulent behavior that the hand gesture is detected. If not, then it appears the language would be “detecting hand gestures that indicate potential fraudulent behavior by analyzing the actions”, or “detecting hand gestures by analyzing the actions; and identifying potential fraudulent behavior from a detected hand gesture along with an identified unexpected object”. Please clarify.
Claim 2 recites “sending an alert when one or more of the actions and the objects”. It is not clear which “objects” the applicant is referring to since the claim language prior recite “objects associated with one or more hands of the operator”, “unexpected objects” and “known objects”. Please clarify.
Claim 2 recites “analyzing the actions to identify potential fraudulent behavior” and “sending an alert when one or more of the actions and the objects indicate a card slot tampering event”. The claim language does not appear to provide a relationship of a fraudulent behavior with a card slot tampering event, if there is one. More specifically, it is unclear if the applicant intends the fraudulent behavior to be a card slot tampering event, or if the card slot tampering event is unrelated to the fraudulent behavior. For example, does the applicant intend “sending an alert when the identified potential fraudulent behavior indicates a card tampering event”? Please clarify.
Claim 2 recites “determining whether the objects are known objects or unknown objects based on visual features extracted from portions of the images” and further recites “identify unexpected objects”. It is not clear if unknown objects and unexpected objects are the same or different. Please clarify. If the same, proper antecedent basis is required since two terms are being used for a same thing. For example, does the applicant intend “identify unknown objects in the one or more hands”. Please clarify. For examination purposes, the term “unexpected” will be interpreted as “unknown”. More specifically, “unexpected object”/”unexpected objects” will be interpreted as “unknown object”/”unknown objects”.
Claim 7 recites “a particular unknown object”. Claim 10 recites “the particular object is known or unknown”. It is unclear if the applicant intends “unknown object” to be the same as, or different than, “unexpected object” in claim 2. Please clarify. If different, then it is unclear if the applicant intends both an unexpected object and a particular unknown object to both be identified/determined. Please clarify.
Claim 14 recites “wherein the foreign object is determined to be an unknown object based on visual features extracted from portions of the images”. However, the claim additionally recites “comparing feature amounts extracted from the images against model features associated with known objects to identify a foreign object”. Therefore, it is not clear if the applicant intends the visual features to be the feat amounts (or features as interpreted for examination purposes) extracted from the images. Please clarify. If so, then proper antecedent basis is needed. If these are different features, then the claim language should better clarify this, e.g. wherein the foreign object is additionally determined to be an unknown object based on visual features extracted from portions of the images” (i.e. determined by feature/feature amounts as well as visual features).
Claims not specifically addressed are indefinite due to their dependency.
Claim Rejections - 35 USC § 103
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.
Claim(s) 2, 3, 7-9, 12, 14, 15, 18, 20 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krebs et al. (US 11,631,068) in view of Rodriguez Bravo et al. (US 2023/0129964) and Kishi (US 2019/0279468).
With respect to claim 2, 7 and 8, Krebs et al. discloses a method comprising:
obtaining images depicting an area adjacent to a transaction terminal and a card reader (106) of the terminal (col. 2, lines 43-61; Fig. 1, 3A, 3B);
determining from the images, actions taken by an operator of the terminal and objects associated with one or more hands of the operator (col. 3, lines 3-16; col. 3, line 51 – col. 5, line 46);
detecting hand gestures by analyzing the actions and identifying potential fraudulent behavior from a detected hand gesture (col. 4, line 44 – col. 5, line 12);
sending an alert when one or more of the actions and objects indicate a card slot tampering event is taking place on the card reader of the terminal (card slot tampering is inherent to person is trying to install an unauthorized device on a card reader) (col. 5, lines 47-58).
Krebs et al. fails to expressly disclose obtaining the images in real time; determining whether the objects are known objects or unknown objects based on visual features extracted from portions of the images; and the alert includes a video clip from the images depicting gestures and actions of the one or more hands when the card slot tampering event is identified. Krebs additionally fails to expressly disclose determining if a particular object is a particular known object or a particular unknown object. Krebs additionally fails to expressly disclose the card slot tampering is detected in real time and halted, and wherein image processing for the detecting is processed exclusively on the transaction terminal by a security agent, exclusively on a cloud or server by a card tampering detection manager, or by the security agent and the card tampering detection manager cooperating with one another to perform the image processing. Based on the following interpretation, Krebs additionally fails to expressly disclose comparing features extracted from the images against model features associated with known objects to identify unknown objects in the one or more hands; and identifying potential fraudulent behavior from an identified unknown object.
Rodriguez Bravo et al. teaches it is well known in the art to determine if an object is a known object or an unknown object based on visual features extracted from portions of the images and to determine whether one or more hands are holding the object (determine that a person is trying to install an unauthorized device on a card reader by determining if an object in a person’s hand is a card (e.g. particular known object) or something else (e.g. particular unknown object which is the object in the hand is not a card) using visual features extracted from an image) ([0038], [0039], [0047], [0063], [0064]). Rodriguez et al. additionally teaches comparing features extracted from the images against model features associated with known objects to identify unknown objects in the one or more hands (using a machine learning model that is trained using training data sets and each of the training data sets being labeled as positive, e.g. an object in a hand is a card, or negative, i.e. an object in a hand is not a card. Thus, features from the images are necessarily compared to model features associated with known objects, i.e. card, to necessarily identify if the object held is a card or not) ([0047]), and the general concept of identifying potential fraudulent behavior from a hand gesture and an identified unknown object ([0046], [0047]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to compare features extracted from the images against model features associated with known objects to identify unknown objects in the one or more hands; and to identify potential fraudulent behavior from both a hand gesture and an identified unknown object, in order to determine if an object in a hand is a card or something else, and to determine an event based on a gesture and an object in the person’s hand, for a more accurate determination of potential fraudulent behavior. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to determine whether objects are known objects or unknown objects based on visual features extracted from portions of the images, and to determine if a particular object is a particular known object or a particular unknown object and determining whether the one or more hands are holding the particular object, in order to determine whether the person is holding a card or something that is not a card near the card reader, as taught by Rodriguez Bravo et al.
The combined teachings of Krebs and Rodriguez Bravo et al. disclose the invention set forth above, however they fail to expressly disclose obtaining the images in real time; and the alert includes a video clip from the images depicting gestures and actions of the one or more hands when the card slot tampering event is identified. The combined teachings additionally fail to expressly disclose card slot tampering is detected in real time and halted, and wherein image processing for the detecting is processed exclusively on the transaction terminal by a security agent, exclusively on a cloud or server by a card tampering detection manager, or by the security agent and the card tampering detection manager cooperating with one another to perform the image processing.
Rodriguez Bravo et al. teaches a system using a machine-learning model with real time data from a camera to capture video data of the area near a card insertion portion, such that the video data can be analyzed using techniques such as image segmentation (thus the video is comprised of images) to determine whether a person at the machine is holding a card or something other than a card, thus allowing the system to determine that a person is holding something that is not a card near the card insertion portion ([0047], [0056]). Kishi et al. teaches it is well known in the art to for card slot tampering to be detected in real time (actual target action data is extracted in real time from video images (actual scene data) being imaged of an anomalous actin of a user in an actual operation) and halted (makes the automated transaction device unusable), and wherein image processing for the detecting is processed exclusively on the transaction terminal (when the surveillance device, which is a computer, is built into a transaction terminal) by a security agent (software, hardware or combination thereof of surveillance device), or exclusively on a cloud or server (when the surveillance device, which is a computer, is remote to the transaction terminal) by a card tampering detection manager (software, hardware or combination thereof of surveillance device) ([0010], [0045], [0055], [0084], [0088], [0139], [0140], Figs. 1 and 15).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to obtain the images in real time and to detect the card slot tampering in real time and to be halted, wherein image processing for the detecting is processed exclusively on the transaction terminal by a security agent, exclusively on a cloud or server by a card tampering detection manager, or by the security agent and the card tampering detection manager cooperating with one another to perform the image processing, in order to detect, in real-time, that a user’s hand(s) is/are engaging in an abnormal activity at the card slot (e.g. detect if the user is tampering with the card slot of the transaction terminal in real time).
The combined teachings of Krebs, Rodriguez Bravo et al. and Kishi et al. disclose the invention set forth above, however they fail to expressly disclose the alert includes a video clip from the images depicting gestures and actions of the one or more hands when the card slot tampering event is identified.
Krebs discloses the images recorded are moving images (functionally equivalent to a video) depicting gestures and actions of the hands of a person that perform actions in front of the transaction terminal, including card slot tampering (a person trying to install an unauthorized device (e.g. shimmer or skimmer) on a card reader) (col. 2, lines 64 – col. 3, line 1; col. 3, lines 54-56). Krebs additionally discloses sending an alert (e.g. message) when one of more of the actions and the objects indicate a card slot tampering event (col. 5, lines 47-58; col. 6 lines 50-57). Although Krebs fails to teach the alert includes a video clip from the images depicting gestures and actions of the one or more hands when the card slot tampering event is identified, Kishi et al. teaches it is well known in the art to record a video of an operator at a card slot and in the event of a card slot tampering event, transmit the video image data to a surveillance center, security agent, or bank employee ([0041], [0045]-[0047], [0054], [0081], [0085], [0087], [0134]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the alert to include a video clip from the images depicting gestures and when the card slot tampering event is identified, in order to retain a video image log of the anomalous actions of the user, e.g. attaching a skimming device, and/or to allow a surveillance agent, security agent, bank employee, etc. to check the video in which the tampering has been detected.
With respect to claim 3, the modified Krebs et al. discloses obtaining the images from a single camera (102) (Krebs: Fig. 1).
With respect to claim 9, the modified Krebs et al. addresses all the limitations of claim 8.
However, the modified Krebs et al. fails to expressly disclose obtaining a transaction state from the terminal.
Kishi et al. teaches it is well known in the art to obtain a transaction state from at terminal ([0036], [0139]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to obtain a transaction state from at terminal in order to identify action items of the user, as taught by Kishi et al. ([0139]).
With respect to claim 12, the modified Krebs et al. addresses all the limitations of claim 2.
However, the modified Krebs et al. fails to expressly disclose capturing an account number on a card detected in images when the card slot tampering event is identified.
Kishi et al. teaches it is well known in the art to capture an account number on a card detected in images when an anomalous action is identified, and the anomalous action can be a card slot tampering event ([0045], [0085])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to capture an account number on a card detected in images when an anomalous action is identified, and the anomalous action can be a card slot tampering event, in order to keep a log and additional information regarding the anomalous action.
With respect to claims 14 and 20, Krebs discloses a system comprising:
a processor (col. 10, lines 50-65);
a memory coupled to the processor (col. 10, lines 50-65); and
the processor configured to perform operations comprising (col. 10, lines 60-65):
analyzing images of an operator present at a terminal captured in real time for identifying a card slot tampering event (card slot tampering is inherent to person is trying to install an unauthorized device on a card reader) (col. 3, lines 3-16; col. 5, lines 32-46);
wherein analyzing includes identifying hand gestures by analyzing actions in the images to identify potential fraudulent behavior (col. 4, line 44 – col. 5, line 12);
raising an alert when the analyzing indicates one or more hands of the operator are adjacent to a card reader of the terminal with a foreign object being held by the operator and indicating that the card slot tampering event has been identified (col. 3, lines 54-56; col. 5, lines 47-58),
wherein the alert causes the terminal to be non-operational for transactions processed on the terminal (col. 5, lines 52-58; col. 9, lines 22-25);
Krebs fails to expressly disclose the images are captured in real time; and the alert includes a video clip from the images depicting gestures and actions of the one or more hands when the card slot tampering event is identified. Krebs additionally fails to expressly disclose the foreign object is determined to be an unknown object based on visual features extracted from portions of the images. Krebs additionally fails to expressly disclose card slot tampering is detected in real time and halted, and wherein image processing for the detecting is processed exclusively on the transaction terminal by a security agent, exclusively on a cloud or server by a card tampering detection manager, or by the security agent and the card tampering detection manager cooperating with one another to perform the image processing. Krebs additionally fails to expressly disclose wherein analyzing includes comparing feature amounts extracted from the images against model features associated with known objects to identify a foreign object; triggering automated actions when the hand gestures indicate potential fraudulent behavior along with a presence of the foreign object.
Rodriguez Bravo et al. teaches it is well known in the art to compare features extracted from the images against model features associated with known objects to identify a foreign object (determine that a person is trying to install an unauthorized device on a card reader by determining if an object in a person’s hand is a card (e.g. particular known object) or something else (using a machine learning model that is trained using training data sets and each of the training data sets being labeled as positive, e.g. an object in a hand is a card, or negative, i.e. an object in a hand is not a card. Thus, features from the images are necessarily compared to model features associated with known objects, i.e. card, to necessarily identify if the object held is a card or not) ([0047]); and triggering automated actions when the hand gestures indicate potential fraudulent behavior along with a presence of the foreign object ([0049]). Rodriguez Bravo et al. teaches it is well known in the art to determine if a foreign object being held by a person is an unknown object (foreign object) based on visual features extracted from portions of the images and to determine whether one or more hands are holding the object (determine that a person is trying to install an unauthorized device on a card reader by determining if an object in a person’s hand is a card or something else using visual features extracted from an image) ([0038], [0039], [0047]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to compare features extracted from the images against model features associated with known objects to identify a foreign object; and to trigger automated actions when the hand gestures indicate potential fraudulent behavior along with presence of the foreign object, in order to determine if an object in a hand is a card or something else, and to perform security actions based on potential fraudulent behavior. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to determine that the foreign object is an unknown object based on visual features extracted from portions of the images, in order to determine whether the person is holding something is not a card near the card reader.
The combined teachings of Krebs and Rodriguez Bravo et al. disclose the invention set forth above, however they fail to expressly disclose the images are captured in real time; and the alert includes a video clip from the images depicting gestures and actions of the one or more hands when the card slot tampering event is identified. The combined teachings additionally fail to expressly disclose card slot tampering is detected in real time and halted, and wherein image processing for the detecting is processed exclusively on the transaction terminal by a security agent, exclusively on a cloud or server by a card tampering detection manager, or by the security agent and the card tampering detection manager cooperating with one another to perform the image processing.
Rodriguez Bravo et al. teaches a system using a machine-learning model with real time data from a camera to capture video data of the area near a card insertion portion, such that the video data can be analyzed using techniques such as image segmentation (thus the video is comprised of images) to determine whether a person at the machine is holding a card or something other than a card, thus allowing the system to determine that a person is holding something that is not a card near the card insertion portion ([0047], [0056]). Kishi et al. teaches it is well known in the art to for card slot tampering to be detected in real time (actual target action data is extracted in real time from video images (actual scene data) being imaged of an anomalous actin of a user in an actual operation) and halted (makes the automated transaction device unusable), and wherein image processing for the detecting is processed exclusively on the transaction terminal (surveillance device when within a transaction terminal) by a security agent (software, hardware or combination thereof of surveillance device), or exclusively on a cloud or server (surveillance device which is a computer when remote to the transaction terminal) by a card tampering detection manager (software, hardware or combination thereof of surveillance device) ([0010], [0045], [0055], [0084], [0088], [0139], [0140], Figs. 1 and 15).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to capture the images in real time and to detect the card slot tampering in real time and to be halted, wherein image processing for the detecting is processed exclusively on the terminal by a security agent, exclusively on a cloud or server by a card tampering detection manager, or by the security agent and the card tampering detection manager cooperating with one another to perform the image processing, in order to detect, in real-time, that a user’s hand(s) is/are engaging in an abnormal activity at the card slot (e.g. detect if the user is tampering with the card slot of the terminal in real time).
The combined teachings of Krebs, Rodriguez Bravo et al. and Farivar et al. disclose the invention set forth above, however they fail to expressly disclose the alert includes a video clip from the images depicting gestures and actions of the one or more hands when the card slot tampering event is identified.
Krebs discloses the images recorded are moving images (functionally equivalent to a video) depicting gestures and actions of the hands of a person that perform actions in front of the transaction terminal, including card slot tampering (a person trying to install an unauthorized device (e.g. shimmer or skimmer) on a card reader) (col. 2, lines 64 – col. 3, line 1; col. 3, lines 54-56). Krebs additionally discloses sending an alert (e.g. message) when one of more of the actions and the objects indicate a card slot tampering event (col. 5, lines 47-58; col. 6 lines 50-57). Although Krebs fails to teach the alert includes a video clip from the images depicting gestures and actions of the one or more hands when the card slot tampering event is identified, Kishi et al. teaches it is well known in the art to record a video of an operator at a card slot and in the event of a card slot tampering event, transmit the video image data to a surveillance center, security agent, or bank employee ([0041], [0045]-[0047], [0054], [0081], [0085], [0087], [0134]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the alert to include a video clip from the images depicting gestures and when the card slot tampering event is identified, in order to retain a video image log of the anomalous actions of the user, e.g. attaching a skimming device, and/or to allow a surveillance agent, security agent, bank employee, etc. to check the video in which the tampering has been detected.
The method is inherent to the system.
With respect to claim 15, the modified Krebs addresses all the limitations of claim 14.
However, the modified Krebs fails to expressly disclose capturing a video clip of the images when the card slot tampering event is identified.
Kishi et al. teaches it is well known in the art to record a video of an operator at a card slot and in the event of a card slot tampering event, the system retains a video clip from the images depicting gestures and actions of the hands of the user ([0041], [0045]-[0047], [0054], [0085], [0134])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to capture a video clip of the images when the card slot tampering event is identified, in order to retain a video image log of the anomalous actions of the user, e.g. attaching a skimming device.
With respect to claim 18, the modified Krebs discloses analyzing further includes obtaining the images from an overhead camera of the terminal (Krebs: col. 2, line 62 - col. 3, line 14; Fig. 1).
With respect to claim 21, the modified Krebs discloses the terminal is an automated teller machine (Krebs: col. 2, lines 40-42).
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krebs et al. modified by Rodriguez Bravo et al. and Kishi et al. as applied to claim 2 above, and further in view of O’Doherty et al. (US 2009/0201372)
With respect to claim 4, the modified Krebs et al. addresses all the limitations of claim 2.
However, the modified Krebs et al. fails to expressly disclose obtaining includes obtaining the images from multiple cameras.
O’Doherty et al. teaches it is well known in the art to obtain images from multiple cameras to determine a card slot tampering event (addition of a skimming device) ([0059]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to try to obtain the images from multiple cameras in order to monitor the card-slot from both a left and right side to detect addition of a skimming device.
Claim(s) 13 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krebs et al. modified by Rodriguez Bravo et al. and Kishi et al. as applied to claims 12 and 15 above, and further in view of Green (US 8,094,026).
With respect to claims 13 and 16, the modified Krebs et al. addresses all the limitations of claims 12 and 15.
However, the modified Krebs et al. fails to expressly disclose providing a link to the video clip when the alert is sent / providing a link to access the video clip.
Green teaches it is well known in the art to alert security and send a link to access the video clip (col. 9, lines 18-21; abstract).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide a link to the video clip when the alert is sent, in order to allow security or law enforcement to view the video clip if desired (see abstract).
Claim(s) 17 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Krebs et al. modified by Rodriguez Bravo et al. and Kishi et al. as applied to claim 14 above, and further in view of Priesterjahn et al. (US 2012/0038773).
With respect to claims 17 and 19, the modified Krebs et al. addresses all the limitations of claim 14, and further discloses obtaining the images from a camera (102) that is situated overhead of the terminal (Krebs: Fig. 1).
However, the modified Krebs et al. fails to expressly disclose also obtaining the images from a first camera located adjacent to the card reader.
Priesterjahn et al. teaches is well known in the art for a terminal to obtain images from a camera located adjacent to a card reader ([0033], [0037], [0038], [0061]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include a camera located adjacent to the card reader, in order to detect actual manipulation in the area of a card reader.
Examiner’s Remarks
With respect to claim(s) 5, 6, 10 and 11, the examiner makes no prior art rejection. However, these claims are not allowable pursuant to the pending Double Patenting rejection.
With respect to claim 5, prior art fails to teach or reasonably suggest, either singly or in combination, determining from the images a distance between the one or more hands and the card reader, in addition to the other limitations of the claims from which claim 5 depends from.
With respect to claim 10, prior art fails to teach or reasonably suggest, either singly or in combination, calculating a risk score based on whether the object is known or unknown, whether the object is being held in the one or more hands, and the transaction state, in addition to the other limitations of the claims from which claim 10 depends from.
Claims not specifically addressed are dependent from claims 5 and 10.
Response to Arguments
Applicant’s arguments with respect to claim(s) 5/4/2026 have been considered but are moot in view of new grounds of rejection in view of the amendments to claims 11 ,14 and 20 (e.g. comparing feature amounts extracted from the images against model features associated with known objects to identify unexpected objects in the one or more hands; detecting hand gestures by analyzing the actions to identify potential fraudulent behavior when a hand gesture indicates potential fraudulent behavior along with an unexpected object).
Applicant's arguments have been fully considered but they are not persuasive.
Regarding the applicant’s argument that the combination of Krebs, Rodriguez Bravo and Kishi do not teach detecting hand gestures that indicate potential fraudulent behavior and triggering actions based on the specific combination of such gestures with unexpected objects, the examiner respectfully disagrees. It is the applicant’s belief that movement pattern of a person’s hands is not detecting hand gestures that indicate fraudulent behavior. The examiner respectfully disagrees. A hand gesture is movement of a hand. Krebs teaches comparing a pattern movement of a person’s hands wit ha set of previously known movement patterns associated with normal behavior, and further describes images can be analyzed in combination with the pattern analysis to determine whether the user is tampering with the kiosk, i.e. fraudulent behavior. Although, Krebs does not teach identifying the object in the person’s hand, Rodriguez Bravo et al. was cited to teach that it is known in the art to detect a hand gesture in addition to known or unknown object in a person’s hand to determine an event (using a machine learning model that is trained using training data sets and each of the training data sets being labeled as positive, e.g. an object in a hand is a card, or negative, i.e. an object in a hand is not a card. Thus, features from the images are necessarily compared to model features associated with known objects, i.e. card, to necessarily identify if the object held is a card or not), and trigger a security action based on the event ([0046], [0047], [0049]). Thus, as described above, the combination of Krebs and Rodriguez Bravo are considered to teach the claimed limitation.
Regarding applicant’s argument that there is no teaching of system architecture recited in the claims, and more specifically the reference(s) do not teach “image processing for the detecting is processed exclusively on the transaction terminal by a security agent, exclusively on a cloud or server by a card tampering detection manager, or by the security agent and the card tampering detection manager cooperating with one another to perform the image processing”. The examiner notes that the claim language is recited in an alternative phrasing. As such, only one of the alternatives is required, not all three. Kishi et al. is considered to teach at least one of the alternatives. More specifically, Kishi et al. teaches a surveillance device (11) which is a computer having an anomaly detection section which can be implemented using software, hardware or combination of software and hardware ([0055]). Kishi et al. teaches that the surveillance device can be remote to an ATM (Fig. 1) (thus can be considered server), or within an ATM (Fig. 15) ([0139], [0140]). The claim fails to define a security agent and a card tampering detection manager, and specification does not specifically define these elements (no special definition provided). Additionally, para. [0048] of the applicant’s specification recites “The software module(s) that implements the method 200 is referred to as a "card slot tampering detection manager. The card slot tampering detection manager is implemented as executable instructions programmed and residing within memory and/or a non-transitory computer-readable (processor-readable) storage medium and executed by one or more processors of a device. The processor(s) of the device that executes the card slot tampering detection manager are specifically configured and programmed to process the card slot tampering detection manager. The card slot tampering detection manager has access to one or more network connections during its processing.", and para. [0080] recites “It should be appreciated that where software is described in a particular form (such as a component or module) this is merely to aid understanding and is not intended to limit how software that implements those functions may be architected or structured. For example, modules are illustrated as separate modules, but may be implemented as homogenous code, as individual components, some, but not all of these modules may be combined, or the functions may be implemented in software structured in any other convenient manner.” As such, hardware, software, or combination thereof, of a generic computer can be considered a security agent or a card tampering detection manager. Therefore, this argument is not persuasive.
Regarding the applicant’s argument that the combination lacks motivation since the motivation is merely statements of the problem to be soled and not proper articulations of why one of ordinary skill in the art would have been motivated to combine the specific teachings of the references in the specific manner to arrive at the claimed invention is not persuasive. For example, modifying Krebs with Rodriguez Bravo’s teaching of determining that an object in a person’s hand is a known object (card) or unknown object (not a card) would be obvious to determine if the object in the person’s hand is a card or not a card. That in combination with a hand gesture would be obvious to one of ordinary skill in the art to determine an event and determine a probability of the even being suspicious or legitimate ([0063], [0064]). The examiner notes that the motivations provided are not mere conclusory statements. Therefore, the applicant’s argument is not persuasive.
Regarding the amended claims recite additional element not addressed by the examiner, the additional elements provided by the newly added limitations are addressed in the rejection above. See above.
In view of the examiner's remarks above, the dependent claims are still rejected in view of their dependency to their independent claims, and the rejection is maintained.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SUEZU ELLIS/Primary Examiner, Art Unit 2876
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