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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Response to Arguments
Applicant's arguments filed 6/12/2026 have been fully considered but they are not persuasive. Applicant argues that the prior art of record Tulloch fails to disclose “a spatial position of a zone of interest of predetermined size in said full-field digital image, and extraction of said zone of interest from said full-field digital image”, and “implementing an obstacle detection module on said extracted zone of interest”. Claim 14 is new and therefore was not considered in the previous office action. However, Examiner disagrees as Tulloch is still effective in rejecting the claims as indicated in the previous non-final rejection. Tulloch discloses that “at least some of the image sensors may have a wide or a panoramic field of view, for example greater than 160° horizontally and/or greater than 75° vertically. What each image sensor can see for any given field of view is of course dictated by where the image sensor is mounted on the aircraft and in which direction it is directed. The predetermined size as recited by the claimed invention is not defined explicitly in the claim language and thus given the broadest reasonable interpretation as the size of the field of view of the image sensors. Furthermore, the UAVs are a type of aircraft and thus interpreted in that fashion. Additionally, Tulloch discloses a method comprising receiving image data representing a first image captured by a first aircraft-mounted image sensor having a first field of view and processing the image data to determine whether an external aerial vehicle candidate (an obstacle) is present in a target space of the first captured space (Tulloch [0003]). The prior art reference Patel is used to teach an obstacle detection module via implementing a neural network to detect and classify obstacles in images having said predetermined size, each obstacle detected being located in said zone of interest (Patel et. al., Figure 3, using machine learning (CNN) that regresses parameters for an equation that best fits a line to detect the horizon, [0041], [0062]).
Lastly, the claim interpretation objection of claims 12-13 under 35 U.S.C. 112(f) is still present due to the use of the nonce term “module”, which has not been corrected. Thus, all claims are still rejected under the prior arts of record Tulloch and Patel.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “module” in claims 12-13.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claim(s) 1-11, 13-14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tulloch (United Kingdom Patent GB 2588893 A).
Regarding claim 1, Tulloch discloses an obstacle detection method implemented by an obstacle detection system on-board an aircraft, the aircraft including at least one on-board camera having an associated field of view, configured to acquire full-field digital images, the method being implemented by a processor of a computation platform (Figures 1a-1b and 2; Summary [0003]), said method comprising:
a)receiving at least one full-field digital image captured by said at least one on-board camera (Summary, [0024-26] e.g., image sensors equipped on aircraft; also, processors equipped within fuselage of aircraft; “first” and “second” captured images are full-field digital image),
b)determining a spatial position of a zone of interest of predetermined size in said full-field digital image, and extraction of said zone of interest from said full-field digital image, and (Tulloch Summary, Figure 5, [0007], [0040] i.e., “target space” is extracted zone of interest)
c)implementing an obstacle detection module on said extracted zone of interest, and implementing a neural network previously trained to detect and classify obstacles in images having said predetermined size, wherein each obstacle detected is located in said zone of interest (Tulloch [0004] one or more stored representations of aerial vehicles is determined by a classifier which is trained to recognize different types of aerial vehicles using supervised training procedures based on images from a library of aerial vehicle images).
Regarding claim 2, Tulloch discloses the method according to claim 1, further comprising a post-processing comprising a computation of a distance between the aircraft and the each detected obstacle and/or a storage of a geo-referenced position, in a fixed terrestrial reference frame, for each detected obstacle belonging to a class of fixed obstacles (Tulloch [0036]-[0037], Figure 4).
Regarding claim 3, Tulloch discloses the method according to claim 1, further comprising repeating the determination of a spatial position of a zone of interest in a same wide field digital image, serving to obtain a plurality of zones of interest in said wide field digital image (Tulloch [0042], Figure 5).
Regarding claim 4, Tulloch discloses the method according to claim 1 further comprising, before determining a spatial position of a zone of interest, acquisition of at least one avionic information item relating to a parameter of motion of the aircraft, and wherein the determination of a spatial position is a function of at least one avionic information item (Tulloch [0037]-[0040], Figure 6, identifying UAVs).
Regarding claim 5, Tulloch discloses the method according to claim 4, wherein said avionic information item comprises a path vector of the aircraft; the zone of interest being centered on a point indicated by the direction of said path vector (Tulloch, [0038]-[0039], triangulation performed based on altitude and ground velocity of the aircraft).
Regarding claim 6, Tulloch discloses the method according to claim 1, wherein the determining a spatial position of a zone of interest comprises receiving a spatial position of a zone of interest using a communication interface with an external system (Tulloch, [0027] sensors may be interconnected and be in communication with one another either directly or via a central system using wireless protocol).
Regarding claim 7, Tulloch discloses the method according to claim 6, wherein the external system is another aircraft (Tulloch, [0041], Figure 5, there is a second aircraft 170 with a plurality of image sensors mounted in similar positions as aircraft 102).
Regarding claim 8, Tulloch discloses the method according to claim 1, wherein the determining a spatial position of a zone of interest comprises receiving a spatial position of a zone of interest from another sensor on-board the aircraft (Tulloch, [0042], Figure 5 and 6).
Regarding claim 9, Tulloch discloses the method according to claim 1, wherein the camera is configured to acquire a succession of full-field digital images forming a video, wherein a) to c) are performed on a subset of acquired digital images spaced apart in time by a given time, and wherein the method further comprises a time tracking of the detected obstacles (Tulloch, [0026] The processor(s) are arranged to process images and/or video captured by the plurality of image sensors to identify external aerial vehicle candidates, such as UAVs. [0034]-[0037] Figure 4 illustrates two overhead images of the ground 138 captured at two different times. The method also includes calculating the velocity of the moving objects based on the difference between reference and their positions in the images relative to static objections, and with the knowledge of the ground velocity and altitude of the aircraft).
Regarding claim 10, Tulloch discloses the method according to claim 1, wherein the spatial position of a zone of interest is determined randomly, and wherein a pseudo-random draw is used to determine respective coordinates of a predetermined point of the zone of interest (Tulloch, [0034]-[0037] non-moving objects in the zone of interest are used as reference to the satellite images and maps of a respective landscape).
Regarding claim 11, Tulloch discloses a computer program comprising software instructions which, when executed by a programmable electronic system, implement the obstacle detection method according to claim 1 (Tulloch, claim 14).
Regarding claim 13, Tulloch discloses the obstacle detection system according to claim 10, further comprising a post-processing module configured to calculate a distance between the aircraft and the or each detected obstacle and/or to store a geo-referenced position, in a fixed terrestrial reference frame, for each detected obstacle belonging to a class of fixed obstacles (Tulloch [0036]-[0037], Figure 4).
Regarding claim 14, the rejection analysis of claim 1 is substantially incorporated herein. Furthermore, Tulloch discloses the spatial position being expressed in a reference- frame associated to said full field digital image, and wherein each obstacle detected is located in said zone of interest, wherein the method further comprises, for each detected obstacle, a computation of a geo-referenced position of said detected obstacle, in a fixed terrestrial reference frame, of coordinates of the said detected obstacle in the reference frame associated to the full field image and of coordinates of the aircraft in said fixed terrestrial reference frame at the time of detection of said detected obstacle, and storage of the geo-referenced position of the detected obstacle (Tulloch [0008], [0032], [0034]-[0035], Figure 4 Optionally, a location of the external aerial vehicle is triangulated using the first and second captured images. Beneficially, this provides location data about the external aerial vehicle which can be used to help minimize the risk the external aerial vehicle poses. Non-moving objects may be identified by reference to the respective locations in the consecutive images and with knowledge of the ground velocity and altitude of the aircraft.).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Tulloch (United Kingdom Patent GB 2588893 A) in view of Patel et. al. (United States Patent US 2022/0198788 A1).
Regarding claim 12, Tulloch discloses an obstacle detection system, suitable for being taken on-board an aircraft, the aircraft comprising at least one on-board camera having an associated field of view, configured to acquire full-field digital images, the obstacle detection system comprising a computation platform comprising at least one processor (See rejection of claim 1) configured to implement: - a module for receiving at least one full-field digital image captured by said at least one on-board camera, - a module for determining a spatial position of a zone of interest of predetermined size in said full-field digital image, and for extracting said zone of interest from said full-field digital image, and (Tulloch Summary, Figures 5 and 6, [0040]). However, Tulloch fails to disclose:
- an obstacle detection module, taking as input, said zone of interest and implementing a neural network previously trained to detect and classify obstacles in images having said predetermined size, wherein each obstacle detected is located in said zone of interest.
Patel teaches an obstacle detection module, taking as input, said zone of interest and implementing a neural network previously trained to detect and classify obstacles in images having said predetermined size, each obstacle detected being located in said zone of interest (Patel et. al. US 2022/0198788 A1, [0041], Figure 3, using machine learning (CNN) that regresses parameters for an equation that best fits a line to detect the horizon. [0062] the detection proposals are input into a neural network (CNN) for further processing to detect and classify dynamic objects and to train the neural network). The obstacle detection module using machine learning in the form of convolutional neural network (CNN) is the key component of the claimed invention. This allows the obstacles to be detected more efficiently and accurately to avoid aircraft collision. Thus, it would have been obvious to one skilled in the art prior to the effective filing date of the claimed invention to have combined the teachings of Tulloch and Patel et. al. so that the CNN algorithm is included in the method of Tulloch.
Conclusion
Response to Amendment
Examiner has carefully considered the applicant’s amendments to the claims, however certain 35 U.S.C 112(f) issues have not been addressed fully, and the prior arts of record are still effective in rejecting all of the claim amendments under broadest reasonable interpretation of the claimed invention. The amendments to the abstract and drawings are sufficient.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JESSICA YIFANG LIN whose telephone number is (571)272-6435. The examiner can normally be reached M-F 7:00am-6:15pm, with optional day off.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vu Le can be reached at 571-272-7332. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JESSICA YIFANG LIN/ Examiner, Art Unit 2668 June 23, 2026
/VU LE/ Supervisory Patent Examiner, Art Unit 2668
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