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 § 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)(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) 1-6 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Li et al. (CN112686864A).
Regarding claim 1, Li discloses a system for detecting leaks comprising: one or more cameras configured to obtain images of one or more objects to be monitored for leaks (note camera device or module throughout the disclosure in Li; page 4 of the translated text also states more than one camera is being used); a processor configured to execute machine readable instructions stored on a memory, which when executed, cause the system to:
receive images from the one or more cameras of the one or more objects to be monitored for leaks (note step S01);
isolate movement in the received images to output isolated movement images (note steps S02 and S03); and
analyze the isolated movement images to determine whether the isolated movement is a leak, a non-leak, or other movement (note steps S04 and S05).
Paragraph bridging in between pages 6 and 7 of the translated text is cited below verbatim:
wherein the decomposing operation of the video material is to generate a plurality of picture materials by means of a timed screenshot. defining the liquid in the picture material, gas leakage area; using image technology to distinguish and classify the picture material, namely dividing into no liquid, normal state of gas leakage and the presence of liquid; the abnormal state of gas leakage. according to the liquid in the picture material; defining the gas running and dripping area; distinguishing the character feature value corresponding to the picture material distinguishing mark under different condition; the character feature value respectively corresponding to the water, oil, steam. For example, by marking tool on line, selecting water drop in the picture material, water column, water stream or oil drop, oil column, oil mist, and white fog of steam, and marking the character characteristic value, water is " water ", oil is " oil ", steam is " steam ". Referring to FIG. 2, after detecting the water leakage condition, the corresponding area is marked; and character value " water " is attached.
According above cited passage, the presence of liquid or gas in an image, such as water, oil, or steam, is considered an detection of movement of the image since leaking liquid or gas are moving substances.
Regarding claim 2, Li inherently discloses the isolated movement images are analyzed using a pretrained convolutional neural network (note the AI model throughout the translated text).
Regarding claim 3, Li inherently discloses the movement is isolated from the received images via an optical flow analysis (note the water column and water stream in above cited passage, they are inherently optical flow of water movements).
Regarding claim 4, Li discloses that the one or more cameras comprises an infrared camera as claimed (note the thermal imaging feature in page 8, last paragraph).
Regarding claims 5 and 6, Li inherently discloses that the isolated movement is analyzed as the non-leak when the isolated movement is below a predetermined threshold and that the isolated movement is analyzed as the leak or the other movement when the isolated movement is above the predetermined threshold. According to Li, “directly capture the dynamic video of the medium when the oil, water, steam leakage, image, comparing with the state in the model to obtain the judging and marking whether there is leakage, at the same time sending alarm prompt.” Page 3, second paragraph. The comparing step inherently includes a threshold so that the leakage of the system is determined based on the threshold.
Claim(s) 1-6 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Korjani et al. (2025/0224081).
Regarding claim 1, Korjani discloses a system for detecting leaks comprising: one or more cameras configured to obtain images of one or more objects to be monitored for leaks (112); a processor configured to execute machine readable instructions stored on a memory (120), which when executed, cause the system to:
receive images from the one or more cameras of the one or more objects to be monitored for leaks (112);
isolate movement in the received images to output isolated movement images (par. 47 and 54); and
analyze the isolated movement images to determine whether the isolated movement is a leak, a non-leak, or other movement (par. 58).
Regarding claim 2, Korjani discloses the isolated movement images are analyzed using a pretrained convolutional neural network (par. 33).
Regarding claim 3, Korjani discloses the movement is isolated from the received images via an optical flow analysis (note par. 47).
Regarding claim 4, Korjani discloses the one or more cameras comprises an infrared camera (note par. 31).
Regarding claim 5, Korjani discloses the isolated movement is analyzed as the non-leak when the isolated movement is below a predetermined threshold (note par. 47). The motion detection algorithms in par. 47 inherently includes a predetermined threshold for determining whether the frame difference is below or above the threshold.
Regarding claim 6, Korjani discloses the isolated movement is analyzed as the leak or the other movement when the isolated movement is above the predetermined threshold (note par. 47). The motion detection algorithms in par. 47 inherently includes a predetermined threshold for determining whether the frame difference is below or above the threshold.
Allowable Subject Matter
Claims 7-11, 13-16, 18-20 are allowed.
Claim 21 is 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.
Response to Arguments
Applicant's arguments filed 5/28/26 have been fully considered but they are not persuasive.
Regarding applicant’s argument that there is no isolation of movement in the obtained images to output isolated movement images as claimed, the examiner disagrees. In page 4, 4th paragraph, Li states an operation of defining the gas running and dripping area. The running and dripping areas depict the movement areas of the gas or liquid in a picture. Furthermore, each of the pictures is marked as water column, water stream, oil drop, oil column, oil mist, or white fog of steam. The markings essentially indicate the types of movements that the liquid or gas is behaving. Thus, the area defining operation and the marking actions isolate the moving liquid or gas pictures from no liquid or gas pictures. The liquid and gas leakage area determination is carried out in step S05 by using AI image learning and identifying. Thus, the marking operations in Li essentially meets the movement isolation limitation as claimed.
Applicant also argues that similar to Li, Korjani also fails to disclose the isolate movement function as claimed, the examiner disagrees. In paragraph 47, Korjani states the following:
Model 121 utilizes its motion detection algorithms to identify motion within the video footage. The motion detection algorithms identify differences in corresponding pixels of different frames in the video to identify the motion. For example, model 121 may identify a first pixel in a first image frame and a corresponding first pixel in a consecutive second image frame and identify motion when the corresponding first pixels in the two frames differ. Model 121 utilizes its equipment detection algorithm to locate tanks 102-104 in the video footage. Model 121 utilizes its leak identification algorithms to determine the presence of leak 105. The gas leak identification algorithm may determine the probability that the detected motion comprises a gas leak based on the long-term background subtraction, the short-term background subtraction, the detected motion, the motion duration, the equipment location, and the telemetry data.
In other words, only the detected motion frames of the video are being used to identify gas leak by the gas leak identification algorithms. Thus, the motion detection algorithms clearly meet the isolate movement limitation as claimed.
In view of above arguments, it is clear that applicant fails to overcome Li and Korjani. As a result, the prior art rejections based on Li and Korjani are maintained.
Conclusion
THIS ACTION IS MADE FINAL. 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 MICHAEL LEE whose telephone number 571-272-7349. The examiner can normally be reached on Monday through Thursday from 9:00 am to 6:00 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, John Miller, can be reached on 571-272-7353. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL LEE/ Primary Examiner,
Art Unit 2422
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