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 .
Applicant’s preliminary amendment filed on January 28, 2025 has been entered and made of record. Currently, claims 2-21 are pending.
Claim Interpretation
Claims 2-13 are not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because they are all method claims.
Claims 18-21 are not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the recitations of “memory”, “processor” and “instructions” provide sufficient structure to perform all claimed limitations.
Claim 14-17 are not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because each of these claims is an article of manufacture claim.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
An obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but an examined application claim is not patentably distinct from the reference claim(s) because the examined claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985). Anticipation is “the ultimate or epitome of obviousness” (In re Kalm, 154 USPQ 10 (CCPA 1967), also In re Dailey, 178 USPQ 293 (CCPA 1973) and In re Pearson, 181 USPQ 641 (CCPA 1974)).
Claims 2-21 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-18 of U.S. Pat. No. 12,125,297 (referred as ‘297 patent hereinafter).
Although the conflicting claims are not identical, they are not patentably distinct from each other because each limitation of the instant claims 2-21 is fully defined by the ‘297 patent. For example, as to the instant claim 2 as a representative claim, claim 1 of the ‘297 patent discloses a method comprising, by one or more computing systems (see lines 1-2):
accessing, from a client system associated with a user, image information comprising textual content in a real-world environment associated with the user (see lines 3-7);
recognizing the textual content (see lines 8-10);
determining, based at least in part upon the image information, a context associated with the real-world environment (see lines 12-14);
identifying a task, wherein the task is identified based at least in part upon the textual content and the determined context (see lines 15-17); and
executing the task (see lines 15-17).
While claim 1 of the ‘297 includes additional limitations (i.e., “dividing…”; “determining, for each of the one or more groups…”) that are not set forth in the instant claim 2, the use of transitional term "comprising/comprises" in the instant claim 2 fails to preclude the possibility of additional elements. Therefore, instant claim 1 fails to define an invention that is patentably distinct from claim 2 of the ‘297 patent.
Furthermore, each of the limitations recited in instant claim 2 is anticipated by patented claim 1 and anticipation is “the ultimate or epitome of obviousness.”
Regarding instant claim 3, claim 1 of the ‘297 patent further discloses wherein the context is associated with a real-world object comprising the textual content (see lines 3-10 and 12-14).
Regarding instant claim 4, claim 1 of the ‘297 patent further discloses wherein the context is associated with a location of the textual content in the real-world environment (see lines 3-10 and 12-14).
Regarding instant claim 5, claim 1 of the ‘297 patent further discloses comprising: sending, to the client system, instructions for presenting a result from executing the task to the user (see lines 18-20).
Regarding instant claim 6, claim 1 of the ‘297 patent further discloses further comprising: sending, to the client system, instructions for presenting an option to execute the task to the user before executing the task (see lines 18-20; also see patented claim 4).
Regarding instant claim 7, claim 2 of the ‘297 patent further discloses comprising: identifying, based on an object-detect model, the real-world object comprising the textual content (see lines 1-6).
Regarding instant claim 8, claim 4 of the ‘297 patent further discloses wherein the task is further identified based on one or more of a user profile associated with the user, social graph information associated with the user, or a user memory associated with the user (see lines 1-6).
Regarding instant claim 9, claim 7 of the ‘297 patent further discloses wherein the image information comprises one or more photographs or videos (see lines 1-2).
Regarding instant claim 10, claim 7 of the ‘297 patent further discloses wherein the image information comprises one or more gaze signals indicating the user is looking at the textual content (see lines 1-3).
Regarding instant claim 11, claim 1 of the ‘297 patent further discloses wherein recognizing the textual content is based at least in part on one or more machine-learning models (see lines 8-10).
Regarding instant claim 12, claim 9 of the ‘297 patent further discloses wherein one or more of the machine-learning models comprise an optical character recognition (OCR) model (see lines 1-3).
Regarding instant claim 13, claim 10 of the ‘297 patent further discloses wherein each of the one or more machine-learning models is based on one or more of a faster region-based convolutional neural network, a hardware-aware efficient design of convolutional neural networks, a radar region proposal network, a residual neural network, a bi-directional long-term short memory network, or a feature pyramid network (see lines 1-7).
Regarding instant claim 14, claim 14 of the ‘297 patent discloses one or more computer-readable non-transitory non-volatile storage media embodying software that is operable when executed by one or more processors to (see lines 1-3):
access, from a client system associated with a user, image information comprising textual content in a real-world environment associated with the user (see lines 4-8);
recognize the textual content (see lines 9-11);
determine, based at least in part upon the image information, a context associated with the real-world environment (see lines 13-15);
identify a task, wherein the task is identified based at least in part upon the textual content and the determined context (see lines 16-18);
execute the task (see lines 16-18); and
send, to the client system, instructions for presenting a result from executing the task to the user (see lines 19-21).
Regarding instant claim 15, claim 14 of the ‘297 patent further discloses wherein the context is associated with a real-world object comprising the textual content (see lines 4-8 and 12-15).
Regarding instant claim 16, claim 14 of the ‘297 patent further discloses wherein the context is associated with a location of the textual content in the real-world environment (see lines 4-8 and 12-15).
Regarding instant claim 17, claim 14 of the ‘297 patent further discloses wherein the software is further operable when executed to: send, to the client system, instructions for presenting an option to execute the task to the user before executing the task (see lines 19-21 and patented claim 16).
Regarding instant claim 18, claim 17 of the ‘297 patent discloses a system comprising: one or more processors; and a non-transitory nonvolatile memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to (see lines 1-4):
access, from a client system associated with a user, image information comprising textual content in a real-world environment associated with the user (see lines 5-9);
recognize the textual content (see lines 10-12);
determine, based at least in part upon the image information, a context associated with the real-world environment (see lines 14-16);
identify a task, wherein the task is identified based at least in part upon the textual content and the determined context (see lines 17-19);
execute the task (see lines 17-19); and
send, to the client system, instructions for presenting a result from executing the task to the user (see lines 20-22).
Regarding instant claim 19, claim 17 of the ‘297 patent further discloses wherein the context is associated with a real-world object comprising the textual content (see lines 5-9 and 13-16).
Regarding instant claim 20, claim 17 of the ‘297 patent further discloses wherein the context is associated with a location of the textual content in the real-world environment (see lines 5-9 and 13-16).
Regarding instant claim 21, claim 17 of the ‘297 patent further discloses wherein the processors are further operable when executing the instructions to: send, to the client system, instructions for presenting an option to execute the task to the user before executing the task (see lines 19-22).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 2-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 2 as a presentative claim, the 101 analysis is presented below.
Step 1: It is noted that claim 2 recites a method which is a process. Thus, claim 2 is directed to one of statutory categories of invention.
Step 2A Prong 1: Limitations (i) “recognizing the textual content”, (ii) “determining, based at least in part upon the image information, a context associated with the real-world environment”, (iii) “identifying a task, wherein the task is identified based at least in part upon the textual content and the determined context”, and (iv) “executing the task” are interpreted as practically performed in the human mind. Therefore, claim 2 recites an abstract idea.
Step 2A Prong 2: It is noted that claim does include any additional limitation “accessing, from a client system associated with a user, image information comprising textual content in a real-world environment associated with the user” that is nothing more than data gathering and thus is insignificant extra-solution activity. The additional limitation does not amount to an integration of the judicial exception into a practical application. Therefore, claim is directed to an abstract idea.
Step 2B: The additional limitation, as pointed out in Step 2A prong 2, are nothing more that data gathering and is insignificant extra-solution activity. These additional limitations, taken individually and/or in combination, do not contribute to an inventive concept and do not amount to significant mor than the judicial exception. Therefore, claim is not a patent eligible.
Claim 18 recites an apparatus and claim 14 recites a manufacture so each of these claims falls within one of the statutory categories of invention. It is noted that each of these claims recites similar claim limitations called for in the counterpart claim 2. Thus, the advanced statements as applied to claim 2 above are incorporated herein. It is also noted that claim 18 recites addition limitations “memory”, and “processor” and “claim 14 recites additional limitations “media” and “computer”. These additional limitations “memory”, “processor”, “medium” and “computer” are recited at a high level of generality such that they amount to no more than mere instructions to implement the abstract idea on a conventional computer. The claims do not point to a specific improvement in computer itself. It is also further noted that each of these claims 18 and 14 recites additional limitations “sending, to the client system, instructions for presenting a result from executing the task to the user” that are nothing more that post-solution activity and is insignificant extra-solution activity. The additional limitations, taken individually and in combination, do not contribute to an inventive concept. Therefore, claims 18 and 14 are also directed to an abstract idea without significantly more.
The advanced statements as applied to claims 1, 14 and 18 above are incorporated hereinafter.
Regarding claim 3, claim limitations “wherein the context is associated with a real-world object comprising the textual content” are interpreted as practically performed in the human mind. Claim does not recites any additional claim limitations that would make it statutory. Thus, claim is not a patent eligible.
Regarding claim 4, claim limitations “wherein the context is associated with a location of the textual content in the real-world environment” are interpreted as practically performed in the human mind. Claim does not recites any additional claim limitations that would make it statutory. Thus, claim is not a patent eligible.
Regarding claim 5, claim limitations “comprising: sending, to the client system, instructions for presenting a result from executing the task to the user” are nothing more that post-solution activity and is insignificant extra-solution activity. Claim does not recites any additional claim limitations that would make it statutory. Thus, claim is not a patent eligible.
Regarding claim 6, claim limitations “further comprising: sending, to the client system, instructions for presenting an option to execute the task to the user before executing the task” are nothing more that post-solution activity and is insignificant extra-solution activity. Claim does not recites any additional claim limitations that would make it statutory. Thus, claim is not a patent eligible.
Regarding claim 7, claim limitations “comprising: identifying, based on an object-detect model, the real-world object comprising the textual content” are interpreted as practically performed in the human mind. Claim does not recites any additional claim limitations that would make it statutory. Thus, claim is not a patent eligible..
Regarding claim 8, claim limitations “wherein the task is further identified based on one or more of a user profile associated with the user, social graph information associated with the user, or a user memory associated with the user” are interpreted as practically performed in the human mind. Claim does not recites any additional claim limitations that would make it statutory. Thus, claim is not a patent eligible.
Regarding claim 9, claim limitations “wherein the image information comprises one or more photographs or videos” are nothing more that data gathering and is insignificant extra-solution activity. Claim does not recites any additional claim limitations that would make it statutory. Thus, claim is not a patent eligible.
Regarding claim 10, claim limitations “wherein the image information comprises one or more gaze signals indicating the user is looking at the textual content” are nothing more that data gathering and is insignificant extra-solution activity. Claim does not recites any additional claim limitations that would make it statutory. Thus, claim is not a patent eligible.
Regarding claim 11, claim limitations “wherein recognizing the textual content is based at least in part on one or more machine-learning models” are interpreted as practically performed in the human mind. The additional claim limitations “machine-learning models” are generic and applied to the abstract ideas in a new environment that is “recognizing the textural content”. These additional limitations, taken individually and/or in combination, do not contribute to an inventive concept and do not amount to significant mor than the judicial exception. Therefore, claim is not a patent eligible.
Regarding claim 12, claim limitations “wherein one or more of the machine-learning models comprise an optical character recognition (OCR) model” are generic and applied to the abstract ideas in a new environment that is “recognizing the textural content”. These additional limitations, taken individually and/or in combination, do not contribute to an inventive concept and do not amount to significant mor than the judicial exception. Therefore, claim is not a patent eligible.
Regarding claim 13, claim limitations “wherein each of the one or more machine-learning models is based on one or more of a faster region-based convolutional neural network, a hardware-aware efficient design of convolutional neural networks, a radar region proposal network, a residual neural network, a bi-directional long-term short memory network, or a feature pyramid network” are generic and applied to the abstract ideas in a new environment that is “recognizing the textural content”. These additional limitations, taken individually and/or in combination, do not contribute to an inventive concept and do not amount to significant mor than the judicial exception. Therefore, claim is not a patent eligible.
send, to the client system, instructions for presenting a result from executing the task to the user (see lines 19-21).
Regarding claim 15, it is noted that claim recites similar claim limitations called for in the counterpart claim 3. Thus, claim is also rejected for the same reasons as set forth in claim 3 above.
Regarding claim 16, it is noted that claim recites similar claim limitations called for in the counterpart claim 4. Thus, claim is also rejected for the same reasons as set forth in claim 4 above..
Regarding claim 17, it is noted that claim recites similar claim limitations called for in the counterpart claim 6. Thus, claim is also rejected for the same reasons as set forth in claim 6 above.
Regarding claim 19, it is noted that claim recites similar claim limitations called for in the counterpart claim 3. Thus, claim is also rejected for the same reasons as set forth in claim 3 above.
Regarding claim 20, it is noted that claim recites similar claim limitations called for in the counterpart claim 4. Thus, claim is also rejected for the same reasons as set forth in claim 4 above..
Regarding claim 21, it is noted that claim recites similar claim limitations called for in the counterpart claim 6. Thus, claim is also rejected for the same reasons as set forth in claim 6 above.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 2-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Khan ("An AI-Based Visual Aid With Integrated Reading Assistant for the Completely Blind," in IEEE Transactions on Human-Machine Systems, vol. 50, no. 6, pp. 507-517, Dec. 2020, Art of record IDS filed on 12/10/2024, referred as Khan hereinafter).
Regarding claim 2 as a representative claim, Khan discloses a method comprising, by one or more computing systems:
accessing, from a client system associated with a first user, image information comprising textual content in a real-world environment associated with the first user (see figures 1-4 & 6; Abstract (i.e., “...The design incorporates a camera and sensors for obstacle avoidance and advanced image processing algorithms for object detection. The distance between the user and the obstacle is measured by the camera as well as ultrasonic sensors. The system includes an integrated reading assistant, in the form of the image-to-text converter, followed by an auditory feedback...”; section III (“DESIGN OF THE PROPOSED DEVICE”), pages 508-511 (i.e., “visual aid for completely blind individuals, with an integrated reading assistant. The setup is mounted on a pair of eyeglasses and can provide real-time auditory feedback to the user through a headphone. Camera and sensors are used for distance measurement between the obstacle and the user” on page 508, right column, 1st paragraph after header “DESIGN OF THE PROPOSED DEVICE”; image sensor and ultrasonic rangefinder are used for acquiring data/information as described in subsection A (“Data Acquisition”) on page 509; TensorFlow employing model zoo (machine learning or AI model from Google) for feature extraction as described in subsection B (Feature Extraction) on pages 509-510).
recognizing the textual content (see subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”): “Tesseract API will extract the texts from the image and save them in a temporary text file. Then it reads out the text from the text file using the text to-speech engine eSpeak. The accuracy of the Tesseract OCR engine depends on ambient lighting and background and usually works well in the white background and brightly illuminated places” described in last paragraph);
determining, based on at least in part upon the image information, a context associated with the first user with respect to the real-world environment (see subsection D (“Objection Detection”) of section III (“DESIGN OF THE PROPOSED DEVICE”) on pages 510-511: “To detect objects in live feeds, we used a Pi camera. Basically, our script sets paths to the model and label maps, loads the model into memory, initializes the Pi camera, and then begins performing object detection on each video frame from the Pi camera. Once the script initializes, which can take up to a maximum of 30 s, a live video stream will begin and common objects inside the view of the user will be identified” described in last paragraph);
identifying a task, wherein the task is identified based at least in part upon the textual content and the determined context and executing a task (see subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”): “Tesseract API will extract the texts from the image and save them in a temporary text file. Then it reads out the text from the text file using the text to-speech engine eSpeak” described in last paragraph).
Regarding claim 14, it is noted that this claim recites similar claim limitations called for in the counterpart claim 1, the advanced statements as applied to claim 1 above are incorporated herein. Khan further discloses additional limitations “media embodying software” (see figure 4 and subsection C (“Workflow of the System”) on page 510: Raspberry Pi hardware and software; section II (“Relevant Work”) on page 508, 2nd paragraph: Raspberry Pi with open computer vision software; (see subsection D (“Objection Detection”) of section III (“DESIGN OF THE PROPOSED DEVICE”) on page 511 left column last paragraph: “To detect objects in live feeds, we used a Pi camera. Basically, our script sets paths to the model and label maps, loads the model into memory, initializes the Pi camera, and then begins performing object detection on each video frame from the Pi camera. Once the script initializes...”).
Regarding claim 18, it is noted that this claim recites similar claim limitations called for in the counterpart claims 1 and 14, the advanced statements as applied to claims 1 and 14 above are incorporated herein. Khan further discloses additional limitations “processor” and “memory” (see figure 4 and subsection C (“Workflow of the System”) on page 510: Raspberry PI hardware and software, wherein the Raspberry Pi is a central processing unit as normally called processor; Figure 1: “Raspberry Pi Processor” and software OpenCV; section II (“Relevant Work”) on page 508, 2nd paragraph: Raspberry Pi with open computer vision software; (see subsection D (“Objection Detection”) of section III (“DESIGN OF THE PROPOSED DEVICE”) on page 511 left column last paragraph: “To detect objects in live feeds, we used a Pi camera. Basically, our script sets paths to the model and label maps, loads the model into memory, initializes the Pi camera, and then begins performing object detection on each video frame from the Pi camera. Once the script initializes...”).
Regarding claim 3, Khan further discloses wherein the context is associated with a real-world object comprising the textual content (see analysis applied to claim 1 above. In addition, as can be seen from figure 6 and subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”), extracting text from image, save it as a text file then read it by using eSpeak to user).
Regarding claim 4, Khan further discloses wherein the context is associated with a location of the textural content in the real-world environment (see analysis applied to claim 1 above. In addition, as can be seen from figure 6 and subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”), extracting text from image, save it as a text file then read it by using eSpeak to user; this implies that text location is inherently included in the image so use could understand when it is read to user vis eSpeak).
Regarding claim 5, Khan further discloses sending, to the client system, instructions for presenting a result from executing the task to the user (see subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”): “Tesseract API will extract the texts from the image and save them in a temporary text file. Then it reads out the text from the text file using the text to-speech engine eSpeak” as described in last paragraph).
Regarding claim 6, Khan further discloses sending, to the client system, instructions for presenting an option to execute the task to the user before executing the task (see subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”): “Tesseract API will extract the texts from the image and save them in a temporary text file. Then it reads out the text from the text file using the text to-speech engine eSpeak” as described in last paragraph; abstract (The system includes an integrated reading assistant, in the form of the image-to-text converter, followed by an auditory feedback); and figure 6).
Regarding claim 7, Khan further discloses comprising:
identifying, based on an object-detect model, the real-world object comprising the textual content (see analysis applied to claim 1 above. In addition, as can be seen from figure 6 and subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”), extracting text from image, save it as a text file then read it by using eSpeak to user).
Regarding claim 8, Khan further discloses wherein the task is identified based on one or more of a user profile associated with the user, social graph information associated with the user, or user memory associated with the user (see figure 6 and subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”), detecting object from each video frame from camera, identifying common objects inside the view of the user, drawing a rectangle around the objects; extracting text from image, save it as a text file which is then read to the user by using eSpeak; abstract (The system includes an integrated reading assistant, in the form of the image-to-text converter, followed by an auditory feedback)).
Regarding claim 9, Khan further discloses wherein the image information comprises one or more photographs or videos (see figure 6 and subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”), detecting object from each video frame from camera, identifying common objects inside the view of the user, drawing a rectangle around the objects; extracting text from image, save it as a text file which is then read to the user by using eSpeak).
Regarding claim 10, while Khan does not specifically discloses wherein the image information comprise one or more gaze signals indicating the first user is looking at the textual content, Khan does disclose that (i)his/her system is mounted on the eyeglasses (see figure 2) of the user who looks at the travel path (figures 11, 12 and 13), (ii)object inside the view of the user will be identified (see page 511 right column, first line) and allowing the user to read text from document (see page 511, right column, subsection E (“Reading Assistant”), 1st full paragraph). Therefore, gaze signals are inherently included in Khan in order to detect object and text for user to read and/or travel.
Regarding claim 11, Khan further discloses wherein recognizing the textual content is based at least in part on one or more machine-learning models (see subsection E (“Reading Assistant”) of section III (“DESIGN OF THE PROPOSED DEVICE”): “Tesseract…includes a highly accurate deep learning-based model…LSTM…recurrent neural network… Tesseract API will extract the texts from the image and save them in a temporary text file. Then it reads out the text from the text file using the text to-speech engine eSpeak. The accuracy of the Tesseract OCR engine depends on ambient lighting and background and usually works well in the white background and brightly illuminated places” as described in last paragraph; also see “TensorFlow” described everywhere in the document).
Regarding claim 12, Khan further discloses wherein the one or more of the machine-learning models comprise an optical character recognition (OCR) model (se figure 6, Tesseract OCR engine).
Regarding claim 13, Khan further discloses wherein each of the one or more machine-learning models is based on one or more of a faster region-based convolutional neural network, a hardware-aware efficient design of convolutional neural networks, a radar region proposal network, a residual neural network, a bi-directional long-term short memory network, or a feature pyramid network (see page 508, left column, 2nd paragraph, CNN; page 510, right column, 1st full paragraph, R-CNN; page 511, right column, paragraph after subsection E (“Reading Assistant”), LSTM; also see “TensorFlow” described everywhere in the document).
Regarding claim 15, it is noted that claim recites similar claim limitations called for in the counterpart claim 3. Thus, claim is also rejected for the same reasons as set forth in claim 3 above.
Regarding claim 16, it is noted that claim recites similar claim limitations called for in the counterpart claim 4. Thus, claim is also rejected for the same reasons as set forth in claim 4 above..
Regarding claim 17, it is noted that claim recites similar claim limitations called for in the counterpart claim 6. Thus, claim is also rejected for the same reasons as set forth in claim 6 above.
Regarding claim 19, it is noted that claim recites similar claim limitations called for in the counterpart claim 3. Thus, claim is also rejected for the same reasons as set forth in claim 3 above.
Regarding claim 20, it is noted that claim recites similar claim limitations called for in the counterpart claim 4. Thus, claim is also rejected for the same reasons as set forth in claim 4 above..
Regarding claim 21, it is noted that claim recites similar claim limitations called for in the counterpart claim 6. Thus, claim is also rejected for the same reasons as set forth in claim 6 above.
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.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Khan.
The advanced statements as applied to claims 2-9 and 11-21 above are incorporated hereinafter.
Regarding claim 10, Khan does not disclose wherein the one or more visual signals comprise one or more gaze signals indicating the first user is looking at the textual content. However, Khan does disclose that his/her system is mounted on the eyeglasses (see figure 2) of the user who looks at the travel path (figures 11, 12 and 13), and object inside the view of the user will be identified (see page 511 right column, first line).
It would have been obvious to include gaze signal in order to properly and correctly detect object and text and translating sound/audio via eSpeak for user to read correctly and travel safely.
Therefore, before the effective filing of the claim invention, it would have been obvious to one of ordinary skill in the include gaze signal in combination with Khan in order to properly and correctly detect object and text and translating them into sound/audio which is spoken out via eSpeak to user so he/she is able to read correctly and travel safely.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DUY M DANG whose telephone number is (571)272-7389. The examiner can normally be reached Monday to Friday from 7:00AM to 3:00PM.
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, Amandeep Saini can be reached at 571-272-3382. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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DMD
8/2026
/DUY M DANG/Primary Examiner, Art Unit 2662
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