Prosecution Insights
Last updated: April 19, 2026
Application No. 18/629,439

ELECTRONIC APPARATUS FOR CLASSIFYING OBJECT REGION AND BACKGROUND REGION AND OPERATING METHOD OF THE ELECTRONIC APPARATUS

Non-Final OA §101§102§103
Filed
Apr 08, 2024
Examiner
MOTSINGER, SEAN T
Art Unit
2673
Tech Center
2600 — Communications
Assignee
Samsung Electronics Co., Ltd.
OA Round
1 (Non-Final)
78%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
90%
With Interview

Examiner Intelligence

Grants 78% — above average
78%
Career Allow Rate
530 granted / 679 resolved
+16.1% vs TC avg
Moderate +11% lift
Without
With
+11.4%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
28 currently pending
Career history
707
Total Applications
across all art units

Statute-Specific Performance

§101
13.1%
-26.9% vs TC avg
§103
41.5%
+1.5% vs TC avg
§102
18.8%
-21.2% vs TC avg
§112
17.8%
-22.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 679 resolved cases

Office Action

§101 §102 §103
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 § 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 1-6, 11- 15 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Re claim 1 The limitation of obtain a first classification map by classifying a first part of the obtained input image as an object region corresponding to the object and a second part of the obtained input image as a background region corresponding to the background of the object;, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example obtaining a classification map in the context of this claim encompasses the user mentally obtaining a classification map. The limitation of pre-process the first classification map to obtain a second classification map in which a noise region in the first classification map is removed;, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example preprocessing in the context of this claim encompasses the user mentally processing a mental map to remove a noise area from the map. The limitation of and obtain an object image corresponding to the object, based on the first classification map and the second classification map, by using the noise region in the first classification map and information about a distance between the camera and the object, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example obtain an image in the context of this claim encompasses the user mentally determining a object image based in the claimed parameters. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements a memory storing at least one instruction; and at least one processor configured to execute the at least one instruction and obtain an input image by capturing an object and a background of the object through a camera. The processor and memory are recited at a high-level of generality (i.e., as a generic processor and generic memory performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The obtaining an input image by capturing an object and a background of the object through a camera is insignificant extra solution activity of capturing an image using a camera. Generic computer components combined with insignificant extra solution activity are not sufficient to integrate the abstract idea into a practical application. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor and memory to perform both the steps amounts to no more than mere instructions to apply the exception using a generic computer component. The obtaining an input image by capturing an object and a background of the object through a camera is insignificant extra solution activity of capturing an image using a camera. Mere instructions to apply an exception using generic computer components combined with insignificant extra solution activity cannot provide an inventive concept. The claim is not patent eligible Re claim 2 The limitation of obtain a final classification map, based on the first classification map and the second classification map, by using the noise region in the first classification map and the information about the distance between the camera and the object; and obtain the object image by applying the final classification map to the input image., as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, obtaining in the context of this claim encompasses the user mentally obtaining a final classification map and mentally applying it to the input image to obtain object image. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends Re claim 3 recites wherein the second classification map is a classification map obtained by performing a morphology process on the first classification map. The examiner notes that morphological operations like dilation and erosion are mathematical operations which morph the object as such this falls into the mathematical concepts abstract idea grouping. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends Re claim 4 The limitation of determine a first correction coefficient based on the information about the distance between the camera and the object, the first correction coefficient comprises a first sub-correction coefficient and a second sub-correction coefficient, as the distance between the camera and the object increases, a magnitude of the first sub-correction coefficient decreases, and as the distance between the camera and the object increases, a magnitude of the second sub-correction coefficient increases,, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, determining the coefficient and sub coefficients in the context of this claim encompasses the user mentally determine coefficients The limitations of obtain the object image based on the first classification map multiplied by the first sub-correction coefficient and the second classification map multiplied by the second sub-correction coefficient belong to the mathematical concepts grouping of abstract ideas. Multiplication is a well-known mathematical concept. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends Re claim 5 The limitation of determine a second correction coefficient based on the noise region, as a ratio of the noise region to the object region in the first classification map increases, a magnitude of the second correction coefficient increases, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, determining a coefficient in the context of this claim encompasses the user mentally determining the coefficient. The limitations of object image based on the second classification map multiplied by the second correction coefficient belong to the mathematical concepts grouping of abstract ideas. Multiplication is a well-known mathematical concept. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends Re claim 6 The limitation of “wherein the second correction coefficient is determined based on at least one of the ratio of the noise region to the object region, a number of noise regions, or an area of the noise region,” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, determining a coefficient in the context of this claim encompasses the user mentally determining the coefficient. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends Re claim 11 The limitation of The limitation of obtain a first classification map by classifying a first part of the obtained input image as an object region corresponding to the object and a second part of the obtained input image as a background region corresponding to the background of the object, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, obtaining a classification map in the context of this claim encompasses the user mentally obtaining a classification map. The limitation of pre-process the first classification map to obtain a second classification map in which a noise region in the first classification map is removed, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, preprocessing in the context of this claim encompasses the user mentally processing a mental map to remove a noise area from the map. The limitation of and obtain an object image corresponding to the object, based on the first classification map and the second classification map, by using the noise region in the first classification map and information about a distance between the camera and the object, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, obtain an image in the context of this claim encompasses the user mentally determining a object image based in the claimed parameters. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements and electronic apparatus and obtaining an input image by capturing an object and a background of the object through a camera. The electronic apparatus is recited at a high-level of generality (i.e., as a generic electronic apparatus performing a generic function) such that it amounts no more than mere instructions to apply the exception using a generic device. The obtaining an input image by capturing an object and a background of the object through a camera is insignificant extra solution activity of capturing an image using a camera. A generic electronic device combined with insignificant extra solution activity are not sufficient to integrate the abstract idea into a practical application. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using an electronic apparatus to perform the steps amounts to no more than mere instructions to apply the exception using a generic electronic device. The obtaining an input image by capturing an object and a background of the object through a camera is insignificant extra solution activity of capturing an image using a camera. Mere instructions to apply an exception using a generic electrical component combined with insignificant extra solution activity cannot provide an inventive concept. The claim is not patent eligible Re claim 12 The limitation of obtaining a final classification map, based on the first classification map and the second classification map, by using the noise region in the first classification map and the information about the distance between the camera and the object, wherein the obtaining of the object image comprises obtaining the object image by applying the final classification map to the input image, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, obtaining in the context of this claim encompasses the user mentally obtaining a final classification map and mentally applying it to the input image to obtain object image. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends. Re claim 13 The limitation of a first correction coefficient determined based on the information about the distance between the camera and the object comprises a first sub-correction coefficient and a second sub-correction coefficient, as the distance between the camera and the object increases, a magnitude of the first sub-correction coefficient decreases, and as the distance between the camera and the object increases, a magnitude of the second sub-correction coefficient increases, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, determining the coefficient and sub coefficients in the context of this claim encompasses the user mentally determine coefficients The limitations of obtaining of the object image comprises obtaining the object image based on the first classification map multiplied by the first sub-correction coefficient and the second classification map multiplied by the second sub-correction coefficient belong to the mathematical concepts grouping of abstract ideas. Multiplication is a well-known mathematical concept. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends Re claim 14 The limitation of as a ratio of the noise region to the object region in the first classification map increases, a magnitude of a second correction coefficient determined based on the noise region increases, , as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, determining a coefficient in the context of this claim encompasses the user mentally determining the coefficient. The limitations of obtaining the object image comprises obtaining the object image based on the second classification map multiplied by the second correction coefficient belong to the mathematical concepts grouping of abstract ideas. Multiplication is a well-known mathematical concept. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends Re claim 15 The limitation of “wherein the second correction coefficient is determined based on at least one of the ratio of the noise region to the object region, a number of noise regions, or an area of the noise region” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, determining a coefficient in the context of this claim encompasses the user mentally determining the coefficient. The analysis with respect to integration into an abstract idea and significantly more are not substantially changed from the claim from which this claim depends. Re claim 20 claim 20 recites the same abstract idea as claim 11. This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements A non-transitory computer-readable recording medium having instructions stored therein, which when executed by a processor in an electronic apparatus cause the processor to perform the operating method and obtain an input image by capturing an object and a background of the object through a camera. The computer readable medium is recited at a high-level of generality (i.e., as a generic computer readable medium performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The obtaining an input image by capturing an object and a background of the object through a camera is insignificant extra solution activity of capturing an image using a camera. Generic computer components combined with insignificant extra solution activity are not sufficient to integrate the abstract idea into a practical application. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using computer readable medium perform the steps amounts to no more than mere instructions to apply the exception using a generic computer component. The obtaining an input image by capturing an object and a background of the object through a camera is insignificant extra solution activity of capturing an image using a camera. Mere instructions to apply an exception using a generic computer component combined with insignificant extra solution activity cannot provide an inventive concept. The claim is not patent eligible Claim Rejections - 35 USC § 102 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)(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. Claim(s) 1-3, 11,12 and 20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by QI et al US 2024/0394893. Re claim 1 Qi discloses An electronic apparatus comprising: a memory storing at least one instruction; and at least one processor configured to execute the at least one instruction to ( see paragraph 7 “An example apparatus can include memory and one or more processors coupled to the memory, the one or more processors being configured to:” note that the invention may be implemented by a processor and memory): obtain an input image by capturing an object and a background of the object through a camera (see paragraph 40 note that images are obtained of a camera see paragraph 49 note that the images can have a foreground and a background); obtain a first classification map by classifying a first part of the obtained input image as an object region corresponding to the object and a second part of the obtained input image as a background region corresponding to the background of the object (see paragraph 60-62 note that each pixel may be classified as foreground or background forming a mask); pre-process the first classification map to obtain a second classification map in which a noise region in the first classification map is removed (see paragraph 63 note that a foreground mask can have noise removed by performing dilation and erosion); and obtain an object image corresponding to the object, based on the first classification map and the second classification map, by using the noise region in the first classification map and information about a distance between the camera and the object (see paragraph 65-67 note that the matching between the segmentation map and the depth map is used to generate final segmentation output see paragraph 74 and 75 note that the segmented frame with depth filtering has a segmented target of interest 612 without background elements 610 see paragraph 61-63 note that the noise filtered version of the foreground mask of the depth map [second classification map] is used in the generation of the final segmentation , this is is based on then noise region and the foreground mask prior to noise removal meaning that the final segmentation map will also be based on these features). Re claim 2 Qi discloses obtain a final classification map, based on the first classification map and the second classification map, by using the noise region in the first classification map and the information about the distance between the camera and the object; (see paragraph 65-67 note that the matching between the segmentation map and the depth map is used to generate final segmentation output including a segmentation map without shapes below a threshold see paragraph 74 and 75 note that the segmented frame with depth filtering has a segmented target of interest 612 without background elements 610 see paragraph 61 note that the noise filtered version of the foreground object is used in the generation of the final segmentation therefore it is based on then noise region and the foreground mask prior to erosion ). and obtain the object image by applying the final classification map to the input image see figure 6 and paragraphs 74 and 75 note that a segmented frame with segmented object 612 is generated) Re claim 3 QI discloses wherein the second classification map is a classification map obtained by performing a morphology process on the first classification map. (see paragraph 63 note that a noise removed foreground mask is generated by applying morphological operations like dilation and erosion). Re claim 11 Qi discloses an operating method of an electronic apparatus, the operating method comprising obtaining an input image by capturing an object and a background of the object through a camera (see paragraph 40 note that images are obtained of a camera see paragraph 49 note that the images can have a foreground and a background); obtaining a first classification map by classifying a first part of the obtained input image as an object region corresponding to the object and a second part of the obtained input image as a background region corresponding to the background of the object (see paragraph 60-62 note that each pixel may be classified as foreground or background forming a mask); pre-processing the first classification map to obtain a second classification map in which a noise region in the first classification map is removed (see paragraph 63 note that a foreground mask can have noise removed by performing dilation and erosion); and obtaining an object image corresponding to the object, based on the first classification map and the second classification map, by using the noise region in the first classification map and information about a distance between the camera and the object (see paragraph 65-67 note that the matching between the segmentation map and the depth map is used to generate final segmentation output see paragraph 74 and 75 note that the segmented frame with depth filtering has a segmented target of interest 612 without background elements 610 see paragraph 61-63 note that the noise filtered version of the foreground mask of the depth map [second classification map] is used in the generation of the final segmentation , this is is based on then noise region and the foreground mask prior to noise removal meaning that the final segmentation map will also be based on these features). Re claim 20 Qi discloses A non-transitory computer-readable recording medium having instructions stored therein, which when executed by a processor in an electronic apparatus cause the processor to perform (see paragraph 6 “a non-transitory computer-readable medium is provided for segmentation with monocular depth estimation. An example non-transitory computer-readable medium can include instructions that, when executed by one or more processors, cause the one or more processors to”) the operating method of claim 11 (see rejection of claim 11). 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 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over QI et al US 2024/0394893 in view of Zhang et al 20240004924 A1. Re claim 2 Qi discloses obtain a final classification map, based on the first classification map and the second classification map, by using the noise region in the first classification map and the information about the distance between the camera and the object; (see paragraph 65-67 note that the matching between the segmentation map and the depth map is used to generate final segmentation output including a segmentation map without shapes below a threshold see paragraph 74 and 75 note that the segmented frame with depth filtering has a segmented target of interest 612 without background elements 610 see paragraph 61 note that the noise filtered version of the foreground object is used in the generation of the final segmentation therefore it is based on then noise region and the foreground mask prior to erosion ) Qi does not expressly disclose and obtain the object image by applying the final classification map to the input image. Zhang discloses obtain the object image by applying the final classification map to the input image (see paragraph 136 extracts the foreground object from the reference image 824 utilizing a segmentation mask generated via a segmentation operation and combines the foreground object with the input digital image 822 utilizing a compositing operation. Note that a segmentation mask may be applied to the reference image to extract the foreground object). The motivation to combine is to generates a composite image 826 by combining one of the foreground objects from the reference image 824 with the background of the input digital image 822 (e.g., by inserting the foreground object into the input digital image 822) (See paragraph 136). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Qi and Zhang to reach the aforementioned advantage. Re claim 12 Qi discloses obtaining a final classification map, based on the first classification map and the second classification map, by using the noise region in the first classification map and the information about the distance between the camera and the object; (see paragraph 65-67 note that the matching between the segmentation map and the depth mask is used to generate final segmentation output including a segmentation map without shapes below a threshold see paragraph 74 and 75 note that the segmented frame with depth filtering has a segmented target of interest 612 without background elements 610 see paragraph 61 note that the noise filtered version of the foreground object is used in the generation of the final segmentation therefore it is based on then noise region and the foreground mask prior to erosion ). Qi does not expressly disclose and wherein the obtaining of the object image comprises obtaining the object image by applying the final classification map to the input image. Zhang discloses wherein the obtaining of the object image comprises obtaining the object image by applying the final classification map to the input image (see paragraph 136 extracts the foreground object from the reference image 824 utilizing a segmentation mask generated via a segmentation operation and combines the foreground object with the input digital image 822 utilizing a compositing operation. Note that a segmentation mask may be applied to the reference image to extract the foreground object). The motivation to combine is to generates a composite image 826 by combining one of the foreground objects from the reference image 824 with the background of the input digital image 822 (e.g., by inserting the foreground object into the input digital image 822) (See paragraph 136). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Qi and Zhang to reach the aforementioned advantage. Allowable Subject Matter Claim 7-10 and 16-19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Cited Art The following is a listing of prior art considered relevant but not applied in a rejection above: Yao US 20100208994 A1 discloses Various implementations relate to improving depth maps. This may be done, for example, by identifying bad depth values and modifying those values. The values may represent, for example, holes and/or noise. According to a general aspect, a segmentation is determined based on an intensity image. The intensity image is associated with a corresponding depth image that includes depth values for corresponding locations in the intensity image. The segmentation is applied to the depth image to segment the depth image into multiple regions. A depth value is modified in the depth image based on the segmentation. A two-stage iterative procedure may be used to improve the segmentation and then modify bad depth values in the improved segmentation, and iterating until a desired level of smoothness is achieved. Both stages may be based, for example, on average depth values in a segment. (See abstract) BARUCH US 20170124717 A1 discloses By a further implementation, a computer-implemented system of background-foreground segmentation for image processing comprises at least one display; at least one memory; at least one processor communicatively coupled to the display and the memory; and a background-foreground segmentation unit operated by the processor and to: obtain pixel data comprising both non-depth data and depth data for at least one image, wherein the non-depth data comprises color data or luminance data or both and associated with the pixels; determine whether a portion of the image is part of a background or foreground of the image based on the depth data and without using the non-depth data; and determine whether a border area between the background and foreground formed by using the depth data are part of the background or foreground depending on the non-depth data without using the depth data. (see paragraph 120) ZOLOTOV; US 20170264880 A1 discloses A device and method of dimensioning using digital images and depth data is provided. The device includes a camera and a depth sensing device whose fields of view generally overlap. Segments of shapes belonging to an object identified in a digital image from the camera are identified. Based on respective depth data, from the depth sensing device, associated with each of the segments of the shapes belonging to the object, it is determined whether each of the segments is associated with a same shape belonging to the object. Once all the segments are processed to determine their respective associations with the shapes of the object in the digital image, dimensions of the object are computed based on the respective depth data and the respective associations of the shapes. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN T MOTSINGER whose telephone number is (571)270-1237. The examiner can normally be reached 9AM-5PM. 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, Chineyere Wills-Burns can be reached at (571) 272-9752. 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. /SEAN T MOTSINGER/Primary Examiner, Art Unit 2673
Read full office action

Prosecution Timeline

Apr 08, 2024
Application Filed
Feb 07, 2026
Non-Final Rejection — §101, §102, §103 (current)

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Expected OA Rounds
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2y 10m
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