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 .
DETAILED ACTION
This action is in response to the applicant's communication filed on 11/08/2024. In virtue of this communication, claims 1-20 filed on 11/08/2024 are currently pending in the instant application.
Drawings
The drawings received on 11/08/2024 have been reviewed by Examiner and they are acceptable.
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.
Claim(s) 1, 9, 11, and 14 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Canini et al. (US 2023/0360398).
As per claim 1, A computing system comprising: one or more processors; ¶[0038] “an imaging device including an imaging sensor having a field of view (FOV) of high resolution, wherein the imaging device is in a fixed position relative to the FOV;” (Canini, ¶[0048] discloses a frame-based sensor has a high-resolution sensor coupled with wide angle optics. ¶[0063] discloses the frame-based sensor may be mounted to a mechanical mounting structure positioned over the conveyor belt. The frame based imaging sensor is fixed relative to its observed FOV.)
“and one or more memories including computer-executable instructions that, when executed by the one or more processors, cause the computing system to:” (Canini, ¶[0124] and ¶[0126].)
“determine a portion of the FOV associated with a position of an object;”(Canini, ¶[0032] discloses event vectors represents X-Y sensor coordinates. ¶[0049] discloses using event data and additional information from the event vector, including the detection of an object, and corresponding region of interest (ROI). )
“activate a portion of the imaging sensor corresponding to the portion of the FOV associated with the position of the object;”(Canini, ¶[0049] discloses selectively activating a frame senor grid selection corresponding to the detected object region.)
“and analyze one or more images captured by the portion of the imaging sensor to identify a feature of the object.”(Canini, ¶[0033] discloses machine vision tasks including feature detection. ¶[0036] discloses applying identification algorithms on frame images. ¶[0049] discloses analyzing the triggered frame sensor section.)
Claim 14 has been analyzed and is rejected for the reasons indicated in claim 1 above.
As pe claim 9, The computing system of claim 1, “wherein the portion of the imaging sensor is a sub-section of a pixel area of the imaging sensor” (Canini, ¶[0049] discloses dividing both frame-based sensor into a grid of smaller sections (subsection of its pixel area), each section of the grid may be analyzed selectively.)
“and wherein the pixel area of the imaging sensor corresponds to the FOV of the imaging sensor.”(Canini, ¶[0030] disclose sensor pixel array, ¶[0050] discloses camera image regions correlated to the sensor FOV, so the pixel area corresponds to FOV.)
As per claim 11, The computing system of claim 1, “wherein the imaging sensor is a first imaging sensor, the computing system further comprising a second sensor configured to capture sensor data associated with the object;”(Canini, ¶[0032] discloses event data from event based sensor ¶[0054] discloses identifying frame based sensor and event based sensor within a system.) “and the one or more memories further including computer-executable instructions that, when executed by the one or more processors, cause the computing system to: determine the position of the object based on the sensor data captured by the second sensor.”(Canini, ¶[0032] discloses event vectors having X-Y coordinate information. ¶[0049] discloses event data and event vector information including detection of an object and corresponding region. ¶[0085] discloses extracting kinematic information (e.g., position and speed) about the parcels running on different sections the observed conveyor belt section. )
As per claim 13, The computing system of claim 1, “wherein the imaging device is included in: a bi-optic imaging station, or a machine vision station.”(Canini, ¶[0111] discloses imaging system is located at a retail checkout station. ¶[0112] discloses the frame-based sensor is located within a housing of a bi-optic barcode reader)
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 non-obviousness.
Claim(s) 2, 5, 12, 15, and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Canini et al. (US 2023/0360398), in view of Sibley et al. (US 2023/0011505).
As per claim 2, The computing system of claim 1, Canini discloses “the one or more memories further including computer-executable instructions that, when executed by the one or more processors, determine the portion of the FOV associated with the position of the object by causing the computing system to: image feature detection” (Canini ¶[0033] discloses vision tasks such as feature detection. Further see ¶[0124] and ¶[0126],)
However Canini does not explicitly disclose the following which would have been obvious in view of Sibley form similar field of endeavor “detect, in an initial image captured by the imaging sensor, an image feature associated with the object; identify the detected image feature across at least two consecutive images; determine, based on the at least two consecutive images, a motion of the object within the FOV; and determine, based on the motion of the object, a predicted position of the object within the FOV, in an image subsequent to the at least two consecutive images, corresponding to the portion of the FOV associated with the position of the object.” (Sibley, ¶[0339] discloses the optical flow may be determined using a number of “control points” that define the object (typically 4 to 6 control points) and relative movement of the control points between successive frames. the optical flow may be used to predict position of the object at some number of frame times in the future. Further discloses selecting the object at a target frame after the N frames based on a targeted position estimate of the object in the target frame.)
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Sibley technique of target object detection into Canini technique to provide the known and expected uses and benefits of Sibley technique over imaging system for object detection technique of Canini. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement. Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Sibley to Canini in order to accurately detect and select target objects . (Refer to Sibley paragraph [0007-0009].)
Claim 15 has been analyzed and is rejected for the reasons indicated in claim 2 above.
As per claim 5, The computing system of claim 1, the one or more memories further including computer-executable instructions that, when executed by the one or more processors, (Canini ¶[0033] discloses vision tasks such as feature detection. Further see ¶[0124] and ¶[0126].)
However Canini does not explicitly disclose the following which would have been obvious in view of Sibley form similar field of endeavor “determine the portion of the FOV associated with the position of the object by causing the computing system to: determine, using an optical flow algorithm and based on at least two consecutive images, a predicted position of the object within
the FOV, in an image subsequent to the at least two consecutive images, corresponding to the portion of the FOV associated with the position of the object.”(Sibley, ¶[0339] discloses the optical flow may be determined using a number of “control points” that define the object (typically 4 to 6 control points) and relative movement of the control points between successive frames. the optical flow may be used to predict position of the object at some number of frame times in the future. Further discloses selecting the object at a target frame after the N frames based on a targeted position estimate of the object in the target frame.)
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Sibley technique of target object detection into Canini technique to provide the known and expected uses and benefits of Sibley technique over imaging system for object detection technique of Canini. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement.
Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Sibley to Canini in order to accurately detect and select target objects . (Refer to Sibley paragraph [0007-0009].)
Claim 17 has been analyzed and is rejected for the reasons indicated in claim 5 above.
As per claim 12, The computing system of claim 11, However Canini does not explicitly disclose the following which would have been obvious in view of Sibley form similar field of endeavor “wherein the second sensor is: a light detection and ranging (LiDAR) sensor, a depth tracking sensor, a time of flight sensor, or an ultra-sonic sensor.”(Sibley, ¶[0128-0129] discloses camera plus other sensors, receive and process image data from image sensors or other components , identify location, pose estimation, or both, of an object in the real world based on the calculations and determinations on the images and other sensor data fused with the image data. ¶[0133] discloses plurality of sensors including LIDAR and calculation of distance to real object based on data received from sensor. The sensing signals from the sensors 432 can also include depth signals from depth sensing cameras. )
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Sibley technique of target object detection into Canini technique to provide the known and expected uses and benefits of Sibley technique over imaging system for object detection technique of Canini. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement. Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Sibley to Canini in order to accurately detect and select target objects . (Refer to Sibley paragraph [0007-0009].)
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Canini et al. (US 2023/0360398), in view of Sibley et al. (US 2023/0011505), further in view of Negro et al. (US 2018/0157882).
As per claim 3, The computing system of claim 2, “wherein detecting the image feature includes detecting at least one of: a barcode, a symbology, one or more corners of an object, or one or more edges of an object.”(Canini, ¶[0033] discloses feature detection task and barcode reading, ¶[0062] discloses The imaging system configured for barcode reading and other image analysis, which may be positioned to have a field-of-view over a conveyor system.)
However Canini as modified by Sibley is silent on the following which would have been obvious in view of Negro form similar field of endeavor “wherein detecting the image feature includes detecting at least one of: a one dimensional barcode, a symbology, one or more corners of an object, or one or more edges of an object.”(Negro, ¶[0024] discloses the disclosed systems and methods can track a single physical linear (barcode) within one or more images or fields-of-view. ¶[0031] discloses detecting candidate with evidence of bars, process the candidates to measure features, for example, edges or evidence for bars.)
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Negro technique of barcode and optical code detection into Canini as modified by Sibley technique to provide the known and expected uses and benefits of Negro technique over imaging system for object detection technique of Canini as modified by Sibley. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement. Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Negro to Canini as modified by Sibley in order to accurately identify optical codes, barcodes and printed labels position on products in motion. (Refer to Negro paragraph [0002-0003].)
Claim(s) 4 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Canini et al. (US 2023/0360398), in view of Sibley et al. (US 2023/0011505), further in view of Hirakawa et al. (US 2013/0271616).
As per claim 4, The computing system of claim 1, the one or more memories further including computer-executable instructions that, when executed by the one or more processors, determine the portion of the FOV associated with the position of the object by causing the computing system to” (Caninin, ¶[0124] and ¶[0126].)
However Canini does not explicitly disclose the following which would have been obvious in view of Sibley form similar field of endeavor “and determine, based on the motion of the object, a predicted position of the object within the FOV, in an image subsequent to the initial image, corresponding to the portion of the FOV associated with the position of the object.”(Sibley, ¶[0338-0339] discloses predicting future position of a target object, various image processing or computer vision algorithms may be used. optical flow may be determined using a number of “control points” that define the object and relative movement of the control points between successive frames. Based on the assumption that rigid object move smoothly, the optical flow may be used to predict position of the object at some number of frame times in the future. Further discloses a target frame after N frames selected corresponding to a position estimate. )
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Sibley technique of target object detection into Canini technique to provide the known and expected uses and benefits of Sibley technique over imaging system for object detection technique of Canini. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement. Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Sibley to Canini in order to accurately detect and select target objects . (Refer to Sibley paragraph [0007-0009].)
However Canini as modified by Sibley does not explicitly disclose the following which would have been obvious in view of Hirakawa form similar field of endeavor “detect, in an initial image captured by the imaging sensor, a blurred image feature associated with the object; determine, based on the blurred image feature, a motion of the object within the FOV;”(Hirakawa, ¶[0039] discloses the motion blur manifests itself as a double edge, where the distance between the double edges corresponds to the speed of the object and motion direction and velocity of moving pixels. ¶[0045] discloses lur angle and length of pixel, ¶[0067] discloses Using the DDWT analysis provides accurate estimates of the length and angle of the motion blur kernel. applications of DDWT include object velocity estimation.)
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Hirakawa technique of detecting motion blurred images into Canini as modified by Sibley technique to provide the known and expected uses and benefits of Hirakawa technique over imaging system for object detection technique of Canini as modified by Sibley. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement.
Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Hirakawa to Canini as modified by Sibley in order to accurately analyze and reconstruct blurred images. (Refer to Hirakawa paragraph [0006].)
Claim 16 has been analyzed and is rejected for the reasons indicated in claim 4 above.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Canini et al. (US 2023/0360398), in view of Sibley et al. (US 2023/0011505), further in view of Kirby (US 2013/0321790).
As per claim 6, The computing system of claim 5, Canini as modified by Sibley does not explicitly disclose the following which would have been obvious in view of Kriby from similar field of endeavor “wherein the imaging sensor is an integrated optical flow imaging sensor.”(Kirby, ¶[0088] discloses integrated optical flow sensor composed of an image sensor and an optical flow processor. ¶[0102] discloses image sensor in integrated optical flow sensor, takes sequential images of surface. )
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Kirby technique of using integrated optical flow image sensor into Canini as modified by Sibley technique to provide the known and expected uses and benefits of Kirby technique over imaging system for object detection technique of Canini as modified by Sibley. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement.
Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Kirby to Canini as modified by Sibley in order to improve the correspondence finding between images. (Refer to Kirby paragraph [00011].)
Claim(s) 7 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Canini et al. (US 2023/0360398), in view of Fjellstad et al. (US 2021/0158000).
As per claim 7, The computing system of claim 1, the one or more memories further including computer-executable instructions that, when executed by the one or more processors, cause the computing system to: (Caninin, ¶[0124] and ¶[0126].)
However Canini does not explicitly disclose the following which would have been obvious in view of Fjellstad form similar field of endeavor “identify a symbology depicted within the identified feature of the object; and decode the symbology depicted within the identified feature of the object.”(Fjellstad, ¶[0037] discloses image capture may be done by positioning the product 122 within the fields of view FOV of the digital imaging sensor(s) housed inside the barcode reader, ¶[0038] discloses the barcode reader 106 captures images of the product 122 using the camera 107, which captures images and generates image data that can be processed to verify that the product ¶[0056] discloses the symbology reader analyzes the images, identifies a barcode in the images, and decodes the barcode to generate a barcode payload as object identification data.)
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Fjellstad technique of symbol reader on product into Canini technique to provide the known and expected uses and benefits of Fjellstad technique over imaging system for object detection technique of Canini. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement. Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Fjellstad to Canini in order to optimize proper product barcode detection. (Refer to Fjellstad paragraph [0002].)
Claim 18 has been analyzed and is rejected for the reasons indicated in claim 7 above.
Claim(s) 8 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Canini et al. (US 2023/0360398), in view of Jin et al. (US 2023/0360645 ).
As per claim 8, The computing system of claim 1, the one or more memories further including computer-executable instructions that, when executed by the one or more processors, cause the computing system to: (Caninin, ¶[0124] and ¶[0126].)
However Canini does not explicitly disclose the following which would have been obvious in view of Jin form similar field of endeavor “identify, using a computer vision algorithm and based on the identified feature of the object, the object.”(Jin, ¶[0072] discloses the electronic apparatus may extract features of the identified object using the learned object detection model and identify the object based on the extracted feature. The electronic apparatus may identify the name of the object using the trained object detection model. For example, the object detection model may be implemented with an artificial intelligence neural network such as a convolutional neural network (CNN), or the like.)
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Jin technique of image processing into Canini technique to provide the known and expected uses and benefits of Jin technique over imaging system for object detection technique of Canini. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement.
Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Jin to Canini in order to provide accurate object detection. (Refer to Jin paragraph [0004].)
Claim 19 has been analyzed and is rejected for the reasons indicated in claim 8 above.
Claim(s) 10 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Canini et al. (US 2023/0360398), in view of Cumoli et al. (US 2016/0300091).
As per claim 10, The computing system of claim 9, the one or more memories further including computer-executable instructions that, when executed by the one or more processors, cause the computing system to” (Canini, ¶[0124] and ¶[0126].)
However, Canini does not explicitly disclose the following which would have been obvious in view of Cumoli form similar field of endeavor “bound the pixel area of the imaging sensor based on the portion of the FOV associated with the position of the object, wherein the pixel area is bound horizontally, bound vertically, or bound both horizontally and vertically.”(Cumoli, ¶[0016] discloses determines a position of an object in the field of view with respect to the direction of travel, Based upon the position of the object in the field of view, and upon a predetermined distance between the object and the optics, the processor defines a region corresponding to a projection to the sensor of the position the object would have in the field of view if the object is at the position in the field of view with respect to the direction of travel and at the predetermined distance from the optics, bounds the image data by the region and analyzes the bounded image data within the region to detect an optical code. ¶[0054] discloses identifying a sensor window start pixel (row/column, horizontal size information, and vertical size information). ¶[0099] discloses the ROI is variable, and can be bounded, in both the y and x direction. )
Before the effective filing date of the claimed invention it would have been obvious to a person of ordinary skill in the art to combine Cumoli technique of code reading in FOV into Canini technique to provide the known and expected uses and benefits of Cumoli technique over imaging system for object detection technique of Canini. The proposed combination would have constituted a mere arrangement of old elements with each performing their known function, the combination yielding no more than one would expect from such an arrangement. Therefore, it would have been obvious to a person of ordinary skill in the art to incorporate Cumoli to Canini in order to accurately detect barcodes and identify corresponding objects on the conveyor.(Refer to Cumoli paragraph [0002].)
Claim 20 has been analyzed and is rejected for the reasons indicated in claim 10 above.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAGHAYEGH AZIMA whose telephone number is (571)272-1459. The examiner can normally be reached Monday-Friday, 9:30-6:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vincent Rudolph can be reached at (571)272-8243. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHAGHAYEGH AZIMA/Examiner, Art Unit 2671
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