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 .
Response to Amendment
The amendment filed October 22, 2025 has been entered. Claims 1-24 remain pending in the application. Applicant’s amendments to the Drawings and Claims have overcome each and every objection previously set forth in the Non-Final Office Action mailed April 22, 2025.
Response to Arguments
Applicant's arguments filed October 22, 2025 have been fully considered but they are not persuasive.
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, the applicant argues that there is no motivation to combine Rady and Kadambi in order to identify defects in the layers of real-world objects because “Kadambi is only directed to surface profilometry, i.e., detecting and profiling surface features and cannot identify sub-surface anomalies of objects that are already in existence” (Page 14 of Remarks). However, Kadambi can identify sub-surface anomalies that are already in existence (Col. 2 lines 58-67, Col. 3 lines 1-3, Col. 37 lines 45-49 – “receiving one or more polarization raw frames of a printed layer of a physical object undergoing additive manufacturing, the one or more polarization raw frames being captured at different polarizations by the one or more polarization cameras; extracting one or more polarization feature maps in one or more polarization representation spaces from the one or more polarization raw frames; obtaining a coarse layer depth map of the printed layer; generating one or more surface-normal images based on the coarse layer depth map and the one or more polarization feature maps; and generating a 3D reconstruction of the printed layer based on the one or more surface-normal images…the layer-by-layer surface profile captured by the surface profilometry system allows the 3D printer to use that information to take corrective action if necessary to improve the print process and correct for any printed anomalies”). While Kadambi is directed to surface profilometry, it detects anomalies layer-by-layer within the object, meaning the detection occurs at a sub-surface level. The object, at least a portion of it, is in existence since it is 3D printed. The goals of Rady and Kadambi may be different, but the concept of identifying anomalies within objects is not a novel idea and may be found in many different fields of work, Kadambi expressing one of them. Additionally, Rady suggests that sub-surface anomaly detection is useful for unique identification of objects since sub-surface anomalies may be more stable (Paragraph 0086 – “C.sub.asset, can vary according to stability of anomaly over time e.g. a crystalline structure such as a diamond has stable anomalies if they reside below surface level of the gem, as such the tolerance may be extremely small compared an asset which experiences decay or growth which is an instability based on time. Additionally, surface level anomalies are much more susceptible to variation, as such the relative depth from surface is a consideration considered for C.sub.asset calculation”). Therefore, a person of ordinary skill in the art could have incorporated Kadambi’s sub-surface anomaly detection concept into Rady’s surface anomaly detection concept and would have done so for the benefit of being able to further uniquely identify and represent the object.
The examiner respectfully disagrees with Applicant's assertion that Miles does not teach and/or disclose:
1) determining a geometric relationship between a range scanner and a spectral imager
2) determining polarimetric radiometric calibration (polarimetric calibration of radiometric readings)
3) spectral imagers.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Rady teaches determining a geometric relationship between a range scanner and a spectral imager (Paragraph 0055, 0058 – “Spectral imager 208 (spectroradiometer) assesses the asset's spectral hypercube data…A calibration target 214 is useful to determine the geometric relationship between the range scanner and the imager”). Miles teaches determining polarimetric radiometric calibration (Col. 7 lines 59-64, Col. 11 lines 11-13, Col. 12 lines 2-4 – “each voxel can be polarimetrically calibrated. The goal of this section is to derive the relationships leading to the single voxel calibration matrix W.sub.n. The first objective is to derive an equation for the measured irradiance… Note a total of 16 irradiance measurements (16 reconstructions) are required to obtain the 4 unknown…Once W.sub.n is obtained for each voxel, the calibration procedure is complete”; Note: polarimetric calibration of radiometric readings occurs. Measuring irradiance is a type of radiometric reading and is required in the calibration), spectral imagers (Col. 3 lines 44-45 – “spectropolarimeter”; Note: a spectropolarimeter is a type of spectral imager), and a polarization calibration target (Col. 7 lines 59-61, Col. 14 lines 1-11, Col. 16 lines 63-67 – “each voxel can be polarimetrically calibrated…The rotating linear polarizer in the calibration facility is rotated by a stepper motor to a position that produces vertical linear polarization. Next, the monochrometer is set to output light at a wavelength in the middle of the range of wavelengths specified by the user and an image of the fiber is acquired. This image is used to adjust the exposure time and then another image is acquired. This image is used to calculate the location of the center of the fiber image on the CCD array. The calibration facility is moved via micrometers in X and Y to center the fiber image on a binned pixel”; Note: the fiber is the polarization calibration target). When these specific parts of Rady and Miles are combined, they teach the limitation: a polarization calibration target to determine a geometric relationship between said range scanner and said spectral imager and perform polarimetric-radiometric calibration. Since Rady already teaches calibration, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Miles to specifically perform polarimetric-radiometric calibration because calibration is a common process performed to correct inaccuracies in polarization involving radiometric measurements, and having a reference point, provided by the fiber, assists in the process. Moreover, since Rady modified by Kadambi already has a calibration target and a polarizer filter, having polarimetric-radiometric calibration would only further improve the accuracy of the data collection.
Claim Objections
Claims 14-22 are objected to because of the following informalities:
Claim 14 recites the limitation “the polarization calibration target” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 21 recites the limitation “said polarizer filter motor” in line 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 21 recites the limitation “said first specimen” in line 11. There is insufficient antecedent basis for this limitation in the claim.
In claim 21 line 22-23, “combine said said” should read “combine said”.
Claim 22 is objected to due to its dependency on claim 21.
Appropriate correction is required.
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.
Claims 1-3, 6-8, and 23-24 are rejected under 35 U.S.C. 103 as being unpatentable over Rady (US 20210126772 A1) in view of Kadambi et al. (US 12099148 B2) and Miles et al. (US 7034938 B1), hereinafter Rady, Kadambi, and Miles respectively.
Regarding claim 1, Rady teaches a device (Paragraph 0007 – “The network node may be configured to use 3D spatial mapping to define the unique signature from spectral analysis data and 3D scan data generated by the item analysis components”; Note: it is implied that there is a device because a network node requires a device to operate) comprising:
one or more processing devices (Paragraph 0062 – “Computing unit(s) 222 provide a processing device or devices”);
a storage device, coupled to the one or more processing devices and storing instructions for execution by at least some of the one or more processing devices (Paragraph 0013 – “a storage device, for example, memory, coupled to the one or more processing devices and storing instructions for execution by at least some of the one or more processing devices”);
a spectral imager to assess the spectral data of a real-world object, identifying anomalies, defects, imperfections, noise and geometric irregularities in composition of the real-world object (Paragraph 0055 – “Spectral imager 208 (spectroradiometer) assesses the asset's spectral hypercube data, identifying irregularities in composition of the asset, notably the radiometric measurements at various spatial frequencies”; Note: assets refer to real-world objects, see paragraph 0043);
a light source to provide broad spectrum illumination on the real-world object (Paragraph 0057 – “Xenon light source 212 provides broad spectrum (flat and uniform) illumination on the asset”);
a range scanner to assess the 3-D spatial data of the real-world object (Paragraph 0056 – “Laser projector and laser receiver 210 (laser range scanner) assesses the 3D spatial data of the object, and geometric irregularities (which may include items such as inclusions in gemstones)”; Note: the laser range scanner is the equivalent to the range scanner);
a calibration target to determine a geometric relationship between said range scanner and said spectral imager and perform calibration (Paragraph 0058 – “A calibration target 214 is useful to determine the geometric relationship between the range scanner and the imager”; Note: it is inherent that calibration is performed if there exists a calibration target);
wherein the one or more processing devices operate to configure the device to generate a digital representation of the real-world object from the spectral analysis data and 3-D scan data (Paragraph 0004, 0007 – “The one or more processing devices operate to configure the network node to: analyze an instance of a physical item using the item analysis components…The network node may be configured to use 3D spatial mapping to define the unique signature from spectral analysis data and 3D scan data generated by the item analysis components”; Note: a physical item is a real-world object. The device generates a unique signature, which is a digital representation, of the real-world object using the spectral analysis data and 3D scan data).
Rady does not teach a device for generating enhanced high-fidelity three-dimensional digital copies of real-world objects; at least one polarizer filter; a polarization calibration target to perform polarimetric-radiometric calibration; “a three-dimensional digital representation” and “polarimetric data” from the limitation: “wherein the one or more processing devices operate to generate a three-dimensional digital representation of the real-world object from the spectral analysis data, 3-D scan data and polarimetric data”; wherein the three-dimensional digital representation of the real-world object identifies and maps surface and sub-surface physical features of the real-world object.
However, Kadambi teaches a device for generating enhanced high-fidelity three-dimensional digital copies of real-world objects (Col. 2 lines 52-67, Col. 3 lines 1-3 – “there is provided a surface profilometry system including: one or more polarization cameras including a polarizing filter, the one or more polarization cameras being configured to capture polarization raw frames at different polarizations; and a processing system including a processor and memory storing instructions that, when executed by the processor, cause the processor to perform: receiving one or more polarization raw frames of a printed layer of a physical object undergoing additive manufacturing…generating a 3D reconstruction of the printed layer based on the one or more surface-normal images”; Note: the surface profilometry system is the equivalent to the device, and it generates a 3D copy of a real-world object); at least one polarizer filter (Col. 7 lines 22-24 – “The polarization camera 10 further includes a polarizer or polarizing filter or polarization mask 16 placed in the optical path between the scene 1 and the image sensor 14”; Note: the polarizing filter is equivalent to the polarizer filter); wherein the one or more processing devices operate to configure the device to generate a three-dimensional digital representation of the real-world object from the polarimetric data (Col. 29 lines 9-16 and 21-29, Col. 38 lines 7-12 – “the physical object fabricated by the 3D printer may be scanned using a stereo polarization camera system according to some embodiments of the present disclosure, and the captured polarization data may be used to assist in the 3D reconstruction of the surfaces of the physical object. This 3D reconstruction can then be compared, in software, to the designed 3D model to detect defects in the 3D printing process… a stereo polarization camera system, such as that described above with respect to FIG. 1D, is used to image an object that is intended to be reconstructed in 3D, e.g., to create a 3D model of the object automatically from the captured polarization raw frames…The processing circuit 100 extracts polarization cues from the polarization raw frames 18 and, with the aid of a coarse layer depth map, generates surface-normal images (also referred to as “normal images”). The processing circuit 100 then generates a corresponding 3D surface profile of the layer being printed”; Note: the processing device generates a 3D representation of the object based on a combination of polarimetric data), wherein the three-dimensional digital representation of the real-world object identifies and maps surface and sub-surface physical features of the real-world object (Col. 2 lines 58-67, Col. 3 lines 1-3, Col. 37 lines 16-19, Col. 37 lines 45-49 – “receiving one or more polarization raw frames of a printed layer of a physical object undergoing additive manufacturing, the one or more polarization raw frames being captured at different polarizations by the one or more polarization cameras; extracting one or more polarization feature maps in one or more polarization representation spaces from the one or more polarization raw frames; obtaining a coarse layer depth map of the printed layer; generating one or more surface-normal images based on the coarse layer depth map and the one or more polarization feature maps; and generating a 3D reconstruction of the printed layer based on the one or more surface-normal images…Surface defects and irregularities may then be detected based on detecting normals that are noisy or erroneous or that otherwise dis-obey pose consistency across the different camera modules of the stereo polarization camera system…the layer-by-layer surface profile captured by the surface profilometry system allows the 3D printer to use that information to take corrective action if necessary to improve the print process and correct for any printed anomalies”; Note: the 3D reconstruction of the object includes surface information about defects, which is a type of physical feature. The layer-by-layer detection implies that the analysis occurs within the object and at a sub-surface level).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to have the device generate 3D copies of real-world objects because it “is important in a variety of contexts, such as quality control in the fabrication and/or manufacturing of objects” (Kadambi: Col. 29 lines 1-20). 3D reconstruction may further assist in the analysis of real-world objects. It also would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to have a polarizer filter for the benefit of better-quality capture of the object and increasing the amount of data that can be used in uniquely identifying the object and in reconstruction. Additionally, since Kadambi collects polarimetric data, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to combine polarimetric data with other data to generate 3D representations of real-world objects because generating 3D representations “is important in a variety of contexts, such as quality control in the fabrication and/or manufacturing of objects” (Kadambi: Col. 29 lines 1-20). As stated before, 3D reconstruction may further assist in the analysis of real-world objects. Since Rady already generates a representation using spectral data and 3D spatial data (Paragraph 0007 – “The network node may be configured to use 3D spatial mapping to define the unique signature from spectral analysis data and 3D scan data generated by the item analysis components”), it would be obvious to include polarimetric data as well to increase the accuracy and quality of the 3D reconstruction. Lastly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to have the 3D representation identify the surface and sub-surface features of the real-world object for the benefit of identifying anomalies on the outside and inside of objects and improving the unique representation of the object through a thorough understanding of both the outside and inside of its structure. Rady already teaches analyzing defects in real-world objects, so to analyze them within the layers of the objects would be even more beneficial in representing the object accurately.
Furthermore, Rady modified by Kadambi still does not teach a polarization calibration target to perform polarimetric-radiometric calibration. However, Miles teaches a polarization calibration target (Col. 7 lines 59-61, Col. 14 lines 1-11, Col. 16 lines 63-67, Col. 17 lines 1-3 – “each voxel can be polarimetrically calibrated…The rotating linear polarizer in the calibration facility is rotated by a stepper motor to a position that produces vertical linear polarization. Next, the monochrometer is set to output light at a wavelength in the middle of the range of wavelengths specified by the user and an image of the fiber is acquired. This image is used to adjust the exposure time and then another image is acquired. This image is used to calculate the location of the center of the fiber image on the CCD array. The calibration facility is moved via micrometers in X and Y to center the fiber image on a binned pixel…The calibration image is positioned for each spatial position (x,y), which entails only one x,y position when shift invariance is determined or assumed. First, a basis state is selected and the calibration is performed using each basis state (block 104). For each spatial position, each spectral wavelength is selected (block 106). The calibration image thus created (.DELTA.x.DELTA.y.DELTA..lamda.) is optically processed in blocks 108 120”; Note: the fiber is the polarization calibration target) to perform polarimetric-radiometric calibration (Col. 7 lines 59-64, Col. 11 lines 11-13, Col. 12 lines 2-4 – “each voxel can be polarimetrically calibrated. The goal of this section is to derive the relationships leading to the single voxel calibration matrix W.sub.n. The first objective is to derive an equation for the measured irradiance… Note a total of 16 irradiance measurements (16 reconstructions) are required to obtain the 4 unknown…Once W.sub.n is obtained for each voxel, the calibration procedure is complete”; Note: polarimetric calibration of radiometric readings occurs. Measuring irradiance is a type of radiometric reading and is required in the calibration). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Miles to specifically have a polarization calibration target because calibration is a common process performed to correct inaccuracies in polarization, and having a reference point, provided by the fiber, assists in the process. Moreover, since Rady modified by Kadambi already have a calibration target and a polarizer filter, performing polarimetric calibration would further improve the accuracy of the data collection.
Regarding claim 2, Rady in view of Kadambi and Miles teach the device of claim 1. Rady further teaches an HD photography camera (Paragraph 0061 – “An HD photography camera 220, for assets (such as gemstones) whose imperfections can't be mapped through the 3DIS alone”); and a scale to determine a mass of the real-world object (Paragraph 0060 – “A scale 218 to determine a mass of the article”; Note: the article is a real-world object).
Regarding claim 3, Rady in view of Kadambi and Miles teach the device of claim 1. Rady further teaches a housing or frame onto or into which said spectral imager, polarizer filter, and range scanner are mounted (Paragraph 0049 – “Item assessment components may be housed in a cabinet and arranged therein to receive a physical item for assessment”; Note: the spectral imager and range scanner are assessment components). Since Rady modified by Kadambi teaches a polarizer filter, the polarizer filter is also considered an item assessment component, and thus, it would be obvious to house the polarizer filter as well.
Regarding claim 6, Rady in view of Kadambi and Miles teach the device of claim 1. Rady further teaches a location determination device configured to receive signals via a communication subsystem with which to determine a position of the device (Paragraph 0063 – “The components that follow, are useful to the meta-data location tracking of an asset which acts as a method of traceability of the asset: Location based services (LBS) device (such as a GPS tracker 224)—allows for the transmission of geolocation data (GPS data) as described in Blockchain for Peer-to-Peer Proof-of-Location. Short range communication component 226 (such as Bluetooth, Bluetooth SMART or ZigBee, Wi-Fi Direct or any other short range network communication mechanism), which will periodically transmit proof-of-location requests and responses”; Note: the LBS device is the equivalent to the location determination device, which receives signals from the short range communication component).
Regarding claim 7, Rady in view of Kadambi and Miles teach the device of claim 1. Rady further teaches wherein the real-world object is a modified real-world object defined from a previously recorded real-world object (Paragraph 0012 – “The instance of a physical item may be a modified physical item defined from a previously recorded physical item”; Note: the physical item is a real-world object).
Regarding claim 8, Rady in view of Kadambi and Miles teach the device of claim 1. Rady further teaches the physical features comprising one or more anomalies, defects, imperfections, geometric features and compositional features of the real-world object (Paragraph 0015 – “the item analysis components may be configured to measure physical features comprising any of anomalies, defects, imperfections, noise and geometric irregularities that are either naturally occurring or human made through a process to produce a unique non-reproducible randomness that uniquely identifies an asset”; Note: the item analysis components include the spectral imager and range scanner, see paragraph 0005). Rady does not teach the “surface and sub-surface physical features” in the limitation: “the surface and sub-surface physical features comprising one or more anomalies, defects, imperfections, geometric features and compositional features of the real-world object”. However, Kadambi teaches surface and sub-surface physical features (Col. 27 lines 64-67, Col. 39 lines 19-26 – “The feature maps 52, 54, and 56 in first polarization representation spaces may then be supplied to a predictor 710 for detecting surface characteristics based on the feature maps 50…the processing circuit 100 performs the method 1100 for each layer, or for each one of a subset of layers, of the object 1006 being printed…The processing circuit 100 then extracts polarization feature maps or polarization images from polarization raw frames”; Note: the physical features of surfaces and sub-surfaces, which are the layers, are measured. The layers are within the object and thus, are at a sub-surface level) comprising one or more anomalies, defects, imperfections, geometric features and compositional features of the real-world object (Col. 19 lines 55-67, Col. 20 lines 1-10, Col. 37 lines 45-49 – “multi-spectral imaging enables material identification and mapping, such as detecting the presence or absence of materials in relief geography, mapping of heavy metals and other toxic wastes in mining areas… Multi-spectral imaging may also be used for material inspection, such as detecting cracks and rust in industrial equipment such as industrial boilers and railway tracks, in which failure can be extremely hazardous and where recovery can be expensive…the layer-by-layer surface profile captured by the surface profilometry system allows the 3D printer to use that information to take corrective action if necessary to improve the print process and correct for any printed anomalies”; Note: the spectral imager and polarizer identifies anomalies and irregularities, like toxic material or cracks, in the composition of real-life objects and its sub-surfaces or layers). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to also analyze the physical features in the surfaces and sub-surfaces of the real-world object for the benefit of identifying anomalies on the inside of objects and improving the unique representation of the object through a thorough understanding of both the outside and inside of its structure. Rady already teaches analyzing defects in real-world objects, so to analyze them within the layers of the objects would be even more beneficial in representing the object accurately.
Regarding claim 23, Rady in view of Kadambi and Miles teaches the device of claim 1. Rady does not teach wherein the three-dimensional representation of the real-world object includes information about structure and composition of individual surface and sub-surface layers of the real-world object. However, Kadambi teaches wherein the three-dimensional representation of the real-world object includes information about structure and composition of individual surface and sub-surface layers of the real-world object (Col. 2 lines 58-67, Col. 3 lines 1-3, Col. 37 lines 16-19, Col. 37 lines 45-49 – “receiving one or more polarization raw frames of a printed layer of a physical object undergoing additive manufacturing, the one or more polarization raw frames being captured at different polarizations by the one or more polarization cameras; extracting one or more polarization feature maps in one or more polarization representation spaces from the one or more polarization raw frames; obtaining a coarse layer depth map of the printed layer; generating one or more surface-normal images based on the coarse layer depth map and the one or more polarization feature maps; and generating a 3D reconstruction of the printed layer based on the one or more surface-normal images…Surface defects and irregularities may then be detected based on detecting normals that are noisy or erroneous or that otherwise dis-obey pose consistency across the different camera modules of the stereo polarization camera system…the layer-by-layer surface profile captured by the surface profilometry system allows the 3D printer to use that information to take corrective action if necessary to improve the print process and correct for any printed anomalies”; Note: the 3D reconstruction of the object includes information about defects and other surface information, which relate to the structure and composition. The layer-by-layer detection implies that the analysis occurs within the object and at a sub-surface level). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to have the 3D representation identify the structure and composition of surface and sub-surface features of the real-world object for the benefit of identifying anomalies on the outside and inside of objects and improving the unique representation of the object through a thorough understanding of both the outside and inside of its structure. Rady already teaches analyzing defects in real-world objects, so to analyze them within the layers of the objects would be even more beneficial in representing the object accurately.
Regarding claim 24, Rady in view of Kadambi and Miles teaches the device of claim 1. Rady does not teach one motor per polarizer for division of time filtering. However, Kadambi teaches a mechanics of rotation per polarizer for division of time filtering (Col. 8 lines 6-11, Col. 8 lines 50-58 – “the polarization mask 16 may include a polarizing filter that rotates mechanically, such that different polarization raw frames are captured by the polarization camera 10 with the polarizing filter mechanically rotated with respect to the lens 12 to transmit light at different angles of polarization to image sensor 14…a polarization camera 10 may move with respect to the scene 1 between different polarization raw frames (e.g., when different raw polarization raw frames corresponding to different angles of polarization are captured at different times, such as in the case of a mechanically rotating polarizing filter), either because the polarization camera 10 has moved or because objects 3 have moved (e.g., if the object is on a moving conveyor system”; Note: the polarizer and polarizer filter can rotate mechanically based on division of time filtering). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to have a way to move the polarizer for the benefit of obtaining a variety of polarization frames at different angles (Kadambi: Col. 9 lines 13-33), which would better capture the object and increase the amount of data that can be used in reconstruction. Rady modified by Kadambi still does not teach the motor. However, Miles teaches a motor per polarizer (Col. 14 lines 1-3 – “The rotating linear polarizer in the calibration facility is rotated by a stepper motor to a position that produces vertical linear polarization”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Miles to have a motor for the polarizer for the benefit of properly positioning the polarizer (Miles: Col. 14 lines 1-3). Rady modified by Kadambi already has a way to move the polarizer, so adding a motor would make the movement easier to control.
Claims 4 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Rady in view of Kadambi, Miles, and Andrew et al. (WO 2017151641 A1), hereinafter Andrew.
Regarding claim 4, Rady in view of Kadambi and Miles teach the device of claim 3. Rady does not teach wherein the housing or frame is capable of flight. However, Andrew teaches wherein the housing is capable of flight (Paragraph 0091 – “FIGS. 5B and 5C illustrate exemplary piloting system 24 for use in the aerial scanning system 10…The sub-cameras 98 may be positioned in a spherical housing 100”; Note: there is housing capable of flight, as it is part of an aerial system). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Andrew to have the housing be capable of flight because scanning tall and large structures can be time-consuming and have safety risks. Using equipment like cranes would be inefficient. Having an aerial scanning system would be the safest and efficient option for scanning large structures (Andrew: Paragraph 0004-0006).
Regarding claim 9, Rady in view of Kadambi and Miles teach the device of claim 1. Rady does not teach wherein the device is configured to capture and optionally export 3-D scan data, spectral analysis data, polarization states S_0, S_1, and S_2 by capturing four polarization angles at a ∈ {0°, 45°, 90°, 135°} or three polarization angles at a ∈ {0°, 90°, 135°} along with an unfiltered capture. However, Andrew teaches wherein the device is configured to capture and optionally export 3-D scan data (Paragraph 0035, 0043 – “the aerial scanning system 10 is configured to provide three-dimensional scans (e.g., maps) of structures…a transmitter 42 (e.g., RF transmitter) of the onboard data processing and transmission system 20 may transmit the processed data to the collection station”; Note: the scan data is captured and exported). Since spectral analysis data, already taught by Rady, and scan data can be captured and exported, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Andrew to capture and export spectral analysis and scan data so that the data can be further used for analysis or in other software or applications. Furthermore, Rady modified by Andrew still does not teach capturing polarization states S_0, S_1, and S_2 by capturing four polarization angles at a ∈ {0°, 45°, 90°, 135°} or three polarization angles at a ∈ {0°, 90°, 135°} along with an unfiltered capture. However, Kadambi teaches polarization states S_0, S_1, and S_2 by capturing four polarization angles at a ∈ {0°, 45°, 90°, 135°} (Col. 21 lines 48-51 – “the four polarization cameras of the first polarization camera module 510-1″ capture light at four different polarization states (e.g., four different linear polarizations of 0°, 45°, 90°, and 135°)”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to have different polarization states by capturing four different polarization angles for the benefit of obtaining a variety of polarization frames at different perspectives (Kadambi: Col. 9 lines 13-33), which would better encompass the object and increase the amount of data that can be used in reconstruction.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Rady in view of Kadambi, Miles, and Kim et al. (3D Imaging Spectroscopy for Measuring Hyperspectral Patterns on Solid Objects), hereinafter Kim.
Regarding claim 5, Rady in view of Kadambi and Miles teach the device of claim 1. Rady does not teach wherein the polarization calibration target is dynamically moveable. However, Kim teaches wherein the polarization calibration target is dynamically movable (Page 7, Fig. 9 caption – “The turntable calibration target”; Note: a turntable is dynamically moveable. The polarization calibration target was previously taught by Rady and Miles in the rejection of claim 1). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kim to have a dynamically moveable calibration target for the benefit of increased accuracy and having multiple perspectives when collecting data on the object.
Claims 10-12 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Rady in view of Kadambi.
Regarding claim 10, Rady teaches a computer implemented method (Paragraph 0013 – “a computer implemented method”) comprising:
measuring and collecting from a real-world object spectral data and 3-D spatial data, using a spectral imager and a range scanner, respectively, (Paragraph 0055-0056 – “Spectral imager 208 (spectroradiometer) assesses the asset's spectral hypercube data, identifying irregularities in composition of the asset, notably the radiometric measurements at various spatial frequencies…Laser projector and laser receiver 210 (laser range scanner) assesses the 3D spatial data of the object, and geometric irregularities (which may include items such as inclusions in gemstones)”; Note: the laser range scanner is the equivalent to the range scanner, and assets refer to real-world objects, see paragraph 0043. It is implied that the spectral data is measured and collected using the spectral imager, and it is implied that the 3D spatial data is measured and collected using the range scanner) through 360 degrees about said real-world object (Paragraph 0005 – “ a mechanism of movement (e.g. a movable platter, platform or gantry) to move the physical item and assessment devices relative to one another to allow a 360-degree assessment of the physical item”; Note: data is measured and collected 360 degrees about the real-world object) under control of computer readable instructions stored on non-transient storage media executed by a processor (Paragraph 0013, 0141 – “memory, coupled to the one or more processing devices and storing instructions for execution by at least some of the one or more processing devices…instructions are stored in a non-transient storage device (e.g. a memory, CD-ROM, DVD-ROM, disc, etc.) to configure a computing device to perform any of the method aspects stored herein”), using said spectral data and said 3-D spatial data to identify surface physical features (Paragraph 0005, 0015, 0046 – “The item analysis components may comprise one or more of: a spectral imager to assess the spectral hypercube data of the physical item, identifying irregularities in composition of the physical item…the item analysis components may be configured to measure physical features comprising any of anomalies, defects, imperfections, noise and geometric irregularities… Such physical features (e.g. anomalies, defects, or imperfections, etc.) may include inclusions, scratches, tears, warps, textual patterns and properties… Analysis data includes spectral imaging data stitched with the 3D spatial information, which captures the previously mentioned anomalies, defects, or imperfections”);
generating, by said processor under control of said computer-readable instructions (Paragraph 0013, 0141 – “memory, coupled to the one or more processing devices and storing instructions for execution by at least some of the one or more processing devices…instructions are stored in a non-transient storage device (e.g. a memory, CD-ROM, DVD-ROM, disc, etc.) to configure a computing device to perform any of the method aspects stored herein”) using said spectral data and said 3-D spatial data, a digital representation of said real-world object (Paragraph 0004, 0007 – “The one or more processing devices operate to configure the network node to: analyze an instance of a physical item using the item analysis components…The network node may be configured to use 3D spatial mapping to define the unique signature from spectral analysis data and 3D scan data generated by the item analysis components”; Note: a physical item is a real-world object. The device generates a unique signature, which is a digital representation, of the real-world object using the spectral analysis data and 3D scan data), said digital representation mapping surface physical features of the real-world object (Paragraph 0046 – “Assessing comprises a 3D spatial mapping to a spectral analysis, specifically looking for physical features (e.g. anomalies, defects, or imperfections which are either naturally occurring, a product of time-based degradation, textual patterns and properties, and/or human made through some process which produces unique non-reproducible randomness) that can uniquely identify an asset. Such physical features (e.g. anomalies, defects, or imperfections, etc.) may include inclusions, scratches, tears, warps, textual patterns and properties…Analysis data includes spectral imaging data stitched with the 3D spatial information, which captures the previously mentioned anomalies, defects, or imperfections (e.g. to define a unique signature)”; Note: the unique signature, which is a digital representation, is defined by a mapping of physical features, like defects).
Rady does not teach generating enhanced high-fidelity three-dimensional digital representations of real-world objects; “polarization states” and “at least one polarizer” from the limitation: “measuring and collecting from a real-world object spectral hypercube data, polarization states, and 3-D spatial data, using a spectral imager, at least one polarizer, and a range scanner”; nor “said polarization states” and “sub-surface physical features” in the limitation: “using said spectral data, said polarization states, and said 3-D spatial data to identify surface and sub-surface physical features of the real-world object; generating, by said processor under control of said computer-readable instructions using said spectral data, said polarization states, and said 3-D spatial data, a digital representation of said real-world object, said digital representation mapping surface and sub-surface physical features of the real-world object”.
However, Kadambi teaches a method for generating enhanced high-fidelity three-dimensional digital representations of real-world objects (Col. 1 lines 66-67, Col. 2 lines 1-14 – “there is provided a method of performing surface profilometry, the method including: receiving one or more polarization raw frames of a printed layer of a physical object…and generating a 3D reconstruction of the printed layer based on the one or more surface-normal images”; Note: 3D representations of real-world objects are generated); measuring and collecting from a real-world object polarization states, using at least one polarizer (Col. 7 lines 22-23, Col. 18 lines 22-25 – “The polarization camera 10 further includes a polarizer or polarizing filter…polarization raw frames corresponding to different polarization states may be captured from different viewpoints when using a polarization camera array that includes multiple polarization cameras”; Note: the polarizer in the polarization camera measured and collects polarization states); using polarization states to identify surface and sub-surface physical features of the real-world object (Col. 19 lines 55-67, Col. 20 lines 1-10, Col. 37 lines 45-49 – “multi-spectral imaging enables material identification and mapping, such as detecting the presence or absence of materials in relief geography, mapping of heavy metals and other toxic wastes in mining areas… Multi-spectral imaging may also be used for material inspection, such as detecting cracks and rust in industrial equipment such as industrial boilers and railway tracks, in which failure can be extremely hazardous and where recovery can be expensive…the layer-by-layer surface profile captured by the surface profilometry system allows the 3D printer to use that information to take corrective action if necessary to improve the print process and correct for any printed anomalies”; Note: the spectral imager and polarizer identifies anomalies and irregularities, like toxic material or cracks, in the composition of real-life objects and its sub-surfaces or layers); generating, by said processor under control of said computer-readable instructions using said polarization states, a digital representation of said real-world object (Col. 29 lines 21-29, Col. 38 lines 7-12 – “a stereo polarization camera system, such as that described above with respect to FIG. 1D, is used to image an object that is intended to be reconstructed in 3D, e.g., to create a 3D model of the object automatically from the captured polarization raw frames… The processing circuit 100 extracts polarization cues from the polarization raw frames 18 and, with the aid of a coarse layer depth map, generates surface-normal images (also referred to as “normal images”). The processing circuit 100 then generates a corresponding 3D surface profile of the layer being printed”; Note: 3D digital representations of objects are generated), said digital representation mapping surface and sub-surface physical features of the real-world object (Col. 27 lines 64-67, Col. 29 lines 21-29, Col. 37 lines 45-49 – “The feature maps 52, 54, and 56 in first polarization representation spaces may then be supplied to a predictor 710 for detecting surface characteristics based on the feature maps 50…a stereo polarization camera system, such as that described above with respect to FIG. 1D, is used to image an object that is intended to be reconstructed in 3D, e.g., to create a 3D model of the object automatically from the captured polarization raw frames. Due to practical manufacturing constraints and/or defects in the manufacturing process, the surface of the object may have sparse irregularities, and may not be ideally smooth. These irregularities may appear as high frequency variations on the surface…the layer-by-layer surface profile captured by the surface profilometry system allows the 3D printer to use that information to take corrective action if necessary to improve the print process and correct for any printed anomalies”; Note: the 3D representation reflects data collected on the physical features, like irregularities, of surfaces. The layer-by-layer detection implies that the analysis occurs within the object and at a sub-surface level.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to collect and measure polarization states using a polarizer for the benefit of collecting better quality image data and obtaining a variety of polarization frames at different angles (Kadambi: Col. 9 lines 13-33), which would help capture the object and increase the amount of data that can be used in reconstruction. It also would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to generate 3D reconstructions of real-world objects because it “is important in a variety of contexts, such as quality control in the fabrication and/or manufacturing of objects” (Kadambi: Col. 29 lines 1-20). 3D reconstruction may further assist in the analysis of real-world objects. Since Rady already generates a representation using spectral data and 3D spatial data (Paragraph 0007 – “The network node may be configured to use 3D spatial mapping to define the unique signature from spectral analysis data and 3D scan data generated by the item analysis components”), it would be obvious to include polarimetric data as well to increase the accuracy and quality of the analysis and reconstruction of the object. Lastly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rady to incorporate the teachings of Kadambi to have the 3D representation identify the surface and sub-surface features of the real-world object for the benefit of identifying anomalies on the outside and inside of objects and improving the unique representation of the object through a thorough understanding of both t