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 .
Election/Restrictions
Applicant’s election without traverse of Group I, claims 1-9 and 14-20 in the reply filed on November 21, 2025 is acknowledged.
Claims 10-13 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected claims, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on November 21, 2025.
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.
Claims 1, 6-8, 14 and 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipate by Ramsay (US Patent No. 9,571,741 B1).
In considering claim 1, Ramsay discloses all the claimed subject matter, note 1) the claimed an image capture device configured to obtain an image is met by the image sensor 114 which captures image and/or video frames (Fig. 1, col. 2, lines 21-59), 2) the claimed a processor configured to recognize an object in the image, calculate a target shutter value corresponding to a movement speed of the object, and determine a shutter value at a starting point of a sensor gain control section in an automatic exposure control process based on the calculated target shutter value is met by the smart shutter controller 180 which adjusts shutter speed and digital gain of a digital camera based on detection of a low-light environment and/or detection of movement of objects in the scene and/or of the camera itself and in response to motion, the adjusted shutter speed and gain are increased relative to the default shutter speed and gain respectively and are selected to result in the same or substantially similar (e.g., within a threshold range) exposure value as the default shutter speed and digital gain pair initially selected by the auto-exposure algorithm, finally, the smart shutter 180 controller applies 250 the adjusted shutter speed and digital gain pair to control the camera (Fig. 3, col. 5, line 35 to col. 6, line 39), and 3) the claimed wherein the shutter value at the starting point of the sensor gain control section is determined to vary between a first shutter value and a second shutter value smaller than the first shutter value depending on the movement speed of the object is met by the smart shutter controller 180 which selects an adjusted shutter speed and digital gain based on processing of the type and magnitude of movement (Figs. 3-4, col. 6, line 14 to col. 8, line 23).
In considering claim 6, the claimed wherein the processor is configured to determine the shutter value at the starting point of the sensor gain control section to converge on the first shutter value as the movement speed of the object is faster, and to determine the shutter value at the staffing point of the sensor gain control section to converge on the second shutter value as the movement speed of the object is slower is met by if no movement in excess of a motion threshold is detected, the smart shutter 180 controller applies 340 the default shutter speed and digital gain, if movement in excess of a motion threshold is detected, the smart shutter controller 180 determines 345 an adjusted shutter speed and digital gain pair,…finally, the smart shutter 180 controller applies 250 the adjusted shutter speed and digital gain pair to control the camera (Figs. 3-4, col. 5, line 35 to col. 6, line 39).
In considering claim 7, the claimed wherein the first shutter value is 1/300 second or more, and the second shutter value is 1/30 second is met by the table illustrates the adjust shutter value and adjusted gain (col. 7, lines 5-67).
In considering claim 8, the claimed wherein, in the automatic exposure control process, the processor is configured to control a shutter speed of the image capture device in a low-illumination section corresponding to the sensor gain control section and a high-illumination section using an iris and a shutter, control the target shutter value according to an automatic exposure control schedule that is inversely proportional as a sensor gain amplification amount increases by passing through the shutter value at the starting point of the sensor gain control section, and wherein the processor is configured to set the automatic exposure control schedule such that the shutter value at the staffing point of the sensor gain control section increases based on the movement speed of the object increasing is met by if the camera is found to be operating in a low-light environment, the smart shutter controller 180 then determines 325 if the luminance of the scene is below a minimum threshold, if so, the camera applies 330 maximum digital gain and minimum shutter speed allowable by the camera 100 in order to maximize exposure,…if movement in excess of a motion threshold is detected, the smart shutter controller 180 determines 345 an adjusted shutter speed and digital gain pair, generally, in response to motion, the adjusted shutter speed and gain are increased relative to the default shutter speed and gain respectively and are selected to result in the same or substantially similar (e.g., within a threshold range) exposure value as the default shutter speed and digital gain pair initially selected by the auto-exposure algorithm and movement data can take multiple forms as face tracking and motion detection algorithms (Figs. 3-4, col. 5, line 35 to col. 6, line 39 and col. 7, line 5 to col. 8, line 56).
Claim 14 is rejected for the same reason as discussed in claim 1 above.
Claim 19 is rejected for the same reason as discussed in claim 6 above.
Claim 20 is rejected for the same reason as discussed in claim 7 above.
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.
Claims 2-4, 9 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Ramsay (US Patent No. 9,571,741 B1) in view of Jang Jeong Hun (KR 102201096 B1).
In considering claim 2, Ramsay discloses all the limitations of the instant invention as discussed in claim 1 above, except for providing the claimed wherein the processor is configured to recognize the object by applying a deep learning-based You Only Look Once (YOLO) algorithm. Jang Jeong Hun teaches that FIG. 4 is a block diagram illustrating an object detection result using a YOLOv3 object detection DCNN model learned to detect a person/vehicle object (Figs. 3-4, page 4, lines 1-48). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the YOLO algorithm as taught by Jang Jeong Hun into Ramsay’s system in order to accurately recognize the object in the image.
In considering claim 3, the claimed wherein the processor is configured to assign an identifier to the object, to extract coordinates of the object, and to calculate an average movement speed of the object based on coordinate information about the object included in a first image frame and a second image frame with a priority lower than the first image frame is met by the object tracking unit 303 based on the bounding box matching of FIG. 5 predicts the positions of the tracking objects in the current frame by using the object tracking information in the previous frame (S501), object tracking information includes [object unique ID, object type] for each object being tracked, and [object bounding box center coordinates, object bounding box width, object bounding box height, object bounding box center velocity vector] Include ] (Figs. 4-5, page 4, lines 1 to page 5, line 42 of Jang Jeong Hun).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 4, the claimed wherein the processor is configured to calculate the target shutter value based on an amount of movement of the object in a unit frame time with respect to a minimum shutter speed of the image capture device and resolution of the camera image is met by the smart shutter controller 180 which selects an adjusted shutter speed and digital gain based on processing of the type and magnitude of movement (Figs. 3-4, col. 6, line 14 to col. 8, line 23 of Ramsay).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 9, Ramsay discloses all the limitations of the instant invention as discussed in claim 1 above, except for providing the claimed further comprising a communication unit, wherein the processor is configured to transmit data of the image to an external server through the communication unit, and receive artificial intelligence-based object recognition results from the external server through the communication unit. Jang Jeong Hun teaches that the controller 1010 is responsible for overall control operations of the communication interface unit 1000, the image analysis unit 1020, and the storage unit 1030 constituting the image analysis apparatus 990 of FIG. 10, the captured image provided by the communication interface unit 1000 may be temporarily stored in the storage unit 1030 and then recalled and provided to the image analysis unit 1020, in addition, the control unit 1010 temporarily stores the analysis result of the captured image by the image analysis unit 1020 in the storage unit 1030, and then transmits it to a control server, etc. to systematically classify and store it in a DB and receives an object detection result using a YOLOv3 object detection DCNN model learned to detect a person/vehicle object (Fig. 10, page 4, lines 1-48 and page 9, line 5 to page 10, line 19). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the communication interface unit as taught by Jang Jeong Hun into Ramsay’s system in order to increase the speed of the system by using an additional server.
Claims 15-17 are rejected for the same reason as discussed in claims 2-4, respectively.
Claims 5 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Ramsay (US Patent No. 9,571,741 B1) in view of Jang Jeong Hun (KR 102201096 B1) and further in view of Gustav Jagbrant et al. (EP 3 611 656 A1).
In considering claim 5, the claimed to calculate the target shutter value that uses the movement speed of the object as input data and automatically calculates the target shutter value according to the movement speed of the object is met by the smart shutter controller 180 which adjusts shutter speed and digital gain of a digital camera based on detection of a low-light environment and/or detection of movement of objects in the scene and/or of the camera itself (Fig. 3, col. 5, line 35 to col. 6, line 39 of Ramsay).
However, the combination of Ramsay and Jang Jeong Hun explicitly do not disclose the claimed wherein the processor is configured to train a learning model by setting performance information corresponding to the resolution of the camera image and speed information about an object recognizable without motion blur as learning data, and to calculate the target shutter value based on the learning model.
Gustav Jagbrant et al. teach that according to the invention, it is suggested that the data processing device determines said exposure setting for said image device by applying a trained model which has been trained to output a suited exposure setting for a given input image taken by said imaging device, e.g., by a camera (page 1, paragraph #0007 to paragraph #0011).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the trained model as taught by Gustav Jagbrant et al. into the combination of Ramsay and Jang Jeong Hun’s system in order to provide an improved vision system that is able to effectively adapt to specific applications and scenarios.
Claim 18 is rejected for the same reason as discussed in claim 5 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tsai (US Patent No. 11,736,807 B2) discloses vehicle image pickup device and image capturing method.
Tran (US Patent No. 11,298,017 B2) discloses medical analysis system.
Haneda (US Patent No. RE42,978 E) discloses image capturing device.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TRANG U TRAN whose telephone number is (571)272-7358. The examiner can normally be reached M-F 10:00AM- 6:00PM.
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December 27, 2025
/TRANG U TRAN/Primary Examiner, Art Unit 2422