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 .
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: Fig. 1, “112”, “114”, “118”.
Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, 9-13, 15-18, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to the judicial exception of mental process type abstract idea (concepts performable in the human mind, including an observation, evaluation, judgement, and opinion) without significantly more.
Independent claims 1, 9, and 15 recites the subject matter,
“determining, by the processor, at least one characteristic value for each pixel in the group of pixels;
determining, by the processor, one or more group attributes representative of the group of pixels based on the at least one characteristic for each pixel in the group of pixels;
determining, by the processor, that the one or more group attributes fails to satisfy a condition associated with a set of predefined threshold group attributes” (claim 1);
“determine at least one characteristic value for each pixel in the group of pixels;
determine one or more group attributes representative of the group of pixels based on the at least one characteristic for each pixel in the group of pixels;
determine whether the one or more group attributes satisfy a condition associated with a set of predefined threshold group attributes” (claim 9); and
“determine at least one characteristic value for each pixel in the group of pixels;
determine one or more group attributes representative of the group of pixels based on the at least one characteristic for each pixel in the group of pixels;
determine whether the one or more group attributes satisfy a condition associated with a set of predefined threshold group attributes” (claim 15).
The noted subject matter of claims 1, 9, and 15 refer to determining at least one characteristic value for each pixel in a selected group of pixels from an image signal, determining a representative group attribute based on the characteristic for each pixel in the group, and determining whether that group attribute satisfies a predefined threshold condition, which are described with a high level of generality which a person may practically perform in the human mind by viewing and evaluating the image signal to mentally determine if a representative group attribute for a selected group of pixels meets a predefined threshold for the group attribute, e.g. noting a group of pixels are not bright enough. Thus, the broadest reasonable interpretation, in light of the specification, of the claimed subject matter directs to performing mental observations and evaluations, falling within the “mental processes” grouping of abstract ideas.
The judicial exceptions of claims 1, 9, and 15 are not integrated into a practical application because the additional claim limitations of,
“receiving, by a processor, an image signal encoding image data of a virtual image to be projected on a surface of a windshield of a vehicle; selecting, by the processor, a group of pixels corresponding to a region of the virtual image; … and in response to determining that the one or more group attributes fails to satisfy the condition, generating, by the processor, a fault detection signal” (claim 1);
“receive an image signal encoding image data of a virtual image to be projected on a surface of a windshield of a vehicle; select a group of pixels from the image signal; … and in response to determination that the one or more group attributes fails to satisfy the condition, generate a fault detection signal” (claim 9); and
“generate an image signal encoding image data of a virtual image; … receive the image signal from the GPU; select a group of pixels from the image signal; … and in response to determination that the one or more group attributes fails to satisfy the condition, generate a fault detection signal” (claim 15)
describe the data gathering steps, selecting particular data source or type of data to be manipulated, and insignificant applications of the noted judicial exception, such that the claims merely add insignificant extra-solution activity to the judicial exceptions. See MPEP 2106.04(d) and MPEP 2106.05(g).
The judicial exception of claims 1, 9, and 15 are further not integrated into a practical application because the additional claim limitations of,
“a processor” (claim 1);
“a memory configured to store a condition associated with a set of predefined threshold group attributes; and a processor” (claim 9); and
“a graphic processing unit (GPU) … ; and a processor” (claim 15) describe generic units performing functions, which given its broadest reasonable interpretation, includes the use of well understood generic computing elements to implement the noted abstract idea with a high level of generality, such that the claims amounts to merely implementing the abstract idea on generic computing elements. See MPEP 2106.04(d), MPEP 2106.05(b), MPEP 2106.05(d)and MPEP 2106.05(f).
The judicial exception of claim 15 is further not integrated into a practical application because the additional claim limitations of, “a surface; a projector configured to project the virtual image on the surface” (claim 15) merely recites the projection of the virtual image on the surface, which generally link the noted judicial exception to the field of heads up displays which project a virtual image onto a surface. See MPEP 2106.04(d) and MPEP 2106.05(h).
Claims 1, 9, and 15 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the above noted additional claim limitations, similarly as discussed above, continue to merely encompass performing additional insignificant extra solution activity to the noted abstract idea activity, and are insufficient to provide significantly more than the noted judicial exceptions. See MPEP 2106.05(g). Claims 1, 9, and 15 above noted additional claim limitations which describe the use of generic computing elements continue to implement the noted abstract idea with a high level of generality, such that the claims amounts to merely implementing the abstract idea on well understood generic computing elements, and are insufficient to provide significantly more than the noted judicial exceptions. See MPEP 2106.05(b), MPEP 2106.05(d), and MPEP 2106.05(f). Claim 15 noted additional claim limitations continue to merely describe generally linking the noted abstract idea to the field of heads up displays, and are insufficient to provide significantly more than the noted judicial exception. See MPEP 2106.05(h).
Furthermore, in consideration of the claims 1, 9, and 15 additional elements as a combination, the additional elements continue to merely perform additional insignificant extra solution activity to the noted abstract idea activity, implementing the abstract idea on generic computing elements, and generally linking the noted abstract idea to the field of heads up displays, and thus do not provide significantly more than the noted judicial exception.
Claims 2-5, 10-13, and 16-18 are not integrated into a practical application because the additional claim limitations of,
“the one or more group attributes comprises a statistical distribution of the at least one characteristic value; and determining the one or more group attributes for the group of pixels comprises binning the at least one characteristic value in a plurality of ranges to generate a histogram corresponding to the group of pixels” (claims 2, 10, and 16);
“wherein the at least one characteristic value is one of a luminance value of a pixel and a color value of a pixel” (claims 3, 11, and 17);
“wherein the one or more group attributes comprises a spatial density of pixels with the at least one characteristic value being greater than a predefined threshold” (claim 4, 12, and 18); and
“wherein the spatial density of pixels is one of: a pixel density; a luminance density; and a color density” (claims 5, 13, and 18),
which are described with a high level of generality, such that the claims amount to selecting particular data source or type of data to be manipulated, such that the claims merely add insignificant extra-solution activity to the judicial exceptions. See MPEP 2106.04(d) and MPEP 2106.05(g).
Claims 2-5, 10-13, and 16-18 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the above noted additional claim limitations, similarly as discussed above, continue to merely encompass performing additional insignificant extra solution activity to the noted abstract idea activity, and are insufficient to provide significantly more than the noted judicial exceptions. See MPEP 2106.05(g). Furthermore, in consideration of the claims 2-5, 10-13, and 16-18 additional elements as a combination, the additional elements continue to merely perform additional insignificant extra solution activity to the noted abstract idea activity, and do not provide significantly more than the noted judicial exception.
Claim 20 is not integrated into a practical application because the additional claim limitations of a “vehicle comprising the system recited in claim 15” merely recites the noted judicial exception being comprised in a vehicle, which generally links the noted judicial exception to a field of use in a vehicle. See MPEP 2106.04(d) and MPEP 2106.05(h).
Claim 20 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the above noted additional claim limitations, similarly as discussed above, continue to merely describe generally linking the noted abstract idea to the field of use of a vehicle, and is insufficient to provide significantly more than the noted judicial exception. See MPEP 2106.05(h). Furthermore, in consideration of the claim 20 additional elements as a combination, the additional elements continue to merely generally link the noted abstract idea to the field of use of a vehicle, and do not provide significantly more than the noted judicial exception.
Examiner notes that claims 6, 14, 19, recite additional features of “amplifying in-band noise in the group of pixels prior to determining the at least one characteristic for each pixel in the group of pixels”, where amplifying the in-band noise of the image signal is directed performing image pre-processing in order to increase energy of the image signal and to performing equalization (see specification [0055]), and the claims recite additional elements which as a whole provides an improvement to the functioning of the heads up display, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP 2106.04(d) and MPEP 2016.05(a).
Thus, claims 6-8, 14, 19, are directed to statutory eligible subject matter.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bhattacharjee et al. (US 2025/0217951, effectively filed 28 Dec. 2023), herein Bhattacharjee in view of Ono et al. (US 2021/0271076), herein Ono, and Correa, Jr. et al. (US 12,248,146, effectively filed 12 February 2024), herein Correa
Regarding claim 1, Bhattacharjee discloses a computer-implemented method for fault detection in heads-up display systems, the method comprising:
receiving, by a processor, an image signal encoding image data of a virtual image (see Bhattacharjee [0018]-[0020], where in a graphics processing unit, image frames are processed);
selecting, by the processor, a group of pixels corresponding to a region of the virtual image (see Bhattacharjee [0018]-[0020], where in a graphics processing unit, image frames are processed on a per-tile basis);
determining, by the processor, at least one characteristic value for each pixel in the group of pixels (see Bhattacharjee [0020], where the luma of each pixel in the frame are determined);
determining, by the processor, one or more group attributes representative of the group of pixels based on the at least one characteristic for each pixel in the group of pixels (see Bhattacharjee [0022]-[0024], where a tile brightness value can be determined for each tile of the frame, a tile histogram can be generated to represent a pixel intensity distribution in the frame, and a tile contrast value can be determined for each tile of the frame);
determining, by the processor, that the one or more group attributes fails to satisfy a condition associated with a set of predefined threshold group attributes (see Bhattacharjee [0024] where threshold are used to determine the points considered as the darkest or brightest bins).
While Bhattacharjee teaches that the display may be embodied as any type of display and includes a heads-up display (see Bhattacharjee [0052]);
Bhattacharjee does not explicitly disclose receiving, by a processor, an image signal encoding image data of a virtual image to be projected on a surface of a windshield of a vehicle.
Ono teaches in a related and pertinent heads up display (HUD) (see Ono Abstract), where an image display device emits light from the HUD which reaches a wind shield which is a projection target member and reflected into the eye of a driver providing a virtual image (see Ono [0028]-[0031]).
At the time of filing, one of ordinary skill in the art would have found it obvious to combine the teachings of Ono with the teachings of Bhattacharjee, such that the contrast enhancement technique taught by Bhattacharjee is performed for the image displayed by the HUD of Ono.
This modification is rationalized as combining prior art elements according to known methods to yield predictable results.
In this instance, Bhattacharjee disclose a base method for performing contrast enhancement that is applicable to any type of display including heads up displays.
Ono teaches a heads up display which emits light from the HUD and reaches a wind shield which is a projection target member and reflected into the eye of a driver providing a virtual image.
One of ordinary skill in the art could have combined the disclosed teachings by using the contrast enhancement technique taught by Bhattacharjee to be performed for the images displayed by the HUD of Ono, and predictably result in a contrast enhancement performed on images displayed by the HUD.
Bhattacharjee and Ono do not explicitly disclose in response to determining that the one or more group attributes fails to satisfy the condition, generating, by the processor, a fault detection signal.
Correa teaches in a related and pertinent heads up display system including a display and processor (see Correa Abstract), where a processor is to output display image and perform monitoring for the displayed images for at least one malfunction, and upon detection of the at least one malfunction, one or more displayed images can be cause to be blank, blank portion, or a blank symbol and can correct the display image data (see Correa col. 7, ln. 5-45).
At the time of filing, one of ordinary skill in the art would have found it obvious to apply the teachings of Correa to the teachings of Bhattacharjee and Ono such that the processors of the heads up display can monitor for display faults, such as images with poor contrast, and generate corresponding fault detection signals and perform a corresponding correction for the display image data, such as contrast enhancement.
This modification is rationalized as an application of a known technique to a known method ready for improvement to yield predictable results.
In this instance, Bhattacharjee and Ono disclose a base method for performing contrast enhancement for the images displayed on a HUD.
Correa teaches a known technique where a processor is to output display image and perform monitoring for the displayed images for at least one malfunction, and detection of the at least one malfunction, one or more displayed images can be cause to be blank, blank portion, or a blank symbol and can correct the display image data
One of ordinary skill in the art would have recognized that by applying Correa’s technique would allow for the method of Bhattacharjee and Ono to use the processors of the heads up display to monitor for display faults, such as images with poor contrast, and generate corresponding fault detection signals and perform a corresponding correction for the display image data, such as contrast enhancement, predictably leading to an improved HUD display.
Regarding claim 2, please see the above rejection of claim 1. Bhattacharjee, Ono, and Correa disclose the computer-implemented method of claim 1, wherein:
one or more group attributes comprises a statistical distribution of the at least one characteristic value (see Bhattacharjee [0022]-[0024], where a tile brightness value can be determined for each tile of the frame, a tile histogram can be generated to represent a pixel intensity distribution in the frame); and
determining the one or more group attributes for the group of pixels comprises binning the at least one characteristic value in a plurality of ranges to generate a histogram corresponding to the group of pixels (see Bhattacharjee [0022]-[0024], where a tile brightness value can be determined for each tile of the frame, a tile histogram can be generated to represent a pixel intensity distribution in the frame).
Regarding claim 3, please see the above rejection of claim 1. Bhattacharjee, Ono, and Correa disclose the computer-implemented method of claim 1, wherein the at least one characteristic value is one of a luminance value of a pixel and a color value of a pixel (see Bhattacharjee [0020], where the luma of each pixel in the frame are determined based on the RGB color intensities).
Regarding claim 4, please see the above rejection of claim 1. Bhattacharjee, Ono, and Correa disclose the computer-implemented method of claim 1, wherein the one or more group attributes comprises a spatial density of pixels with the at least one characteristic value being greater than a predefined threshold (see Bhattacharjee [0024] where thresholds are used to determine the points considered as the darkest or brightest bins).
Regarding claim 5, please see the above rejection of claim 4. Bhattacharjee, Ono, and Correa disclose the computer-implemented method of claim 4, wherein the spatial density of pixels is one of:
a pixel density;
a luminance density (see Bhattacharjee [0023]-[0024], where the histogram includes bins of the luma values for a tile and can represent a luminance density); and
a color density.
Regarding claim 6, please see the above rejection of claim 1. Bhattacharjee, Ono, and Correa disclose the computer-implemented method of claim 1, further comprising amplifying in-band noise in the group of pixels prior to determining the at least one characteristic for each pixel in the group of pixels (see Bhattacharjee [0026], where the contrast of each tile can be enhanced using configurable look up tables for enhancement factors).
Regarding claim 7, please see the above rejection of claim 6. Bhattacharjee, Ono, and Correa disclose the computer-implemented method of claim 6, wherein amplifying the in-band noise is based on a statistical distribution of pixels in the group of pixels with a luminance value greater than a predefined threshold (see Bhattacharjee [0037]-[0041], where the enhancement factors may be obtained from look up tables based on the tile brightness and contrast values).
Regarding claim 8, please see the above rejection of claim 6. Bhattacharjee, Ono, and Correa disclose the computer-implemented method of claim 6, wherein amplifying the in-band noise comprises applying, by the processor, one of a piece-wise linear transfer function and a boxcar filter on the image signal (see Bhattacharjee Fig. 2B and [0031], where the FBLUT has piece-wise points ).
Regarding claim 9, it recites a system performing the method of claim 1. Bhattacharjee, Ono, and Correa teach a system performing the method of claim 1 (see Bhattacharjee [0044]). Please see above for detailed claim analysis, with the exception to the following further limitations:
a memory configured to store a condition associated with a set of predefined threshold group attributes; and a processor (see Bhattacharjee [0044], where the computing device includes a processor and memory, where the memory stores various data and software for the operations of the computing device)
Please see the above rejection for claim 1, as the rationale to combine the teachings of Bhattacharjee, Ono, and Correa are similar, mutatis mutandis.
Regarding claim 10, see above rejection for claim 9. It is a system claim reciting similar subject matter as claim 2. Please see above claim 2 for detailed claim analysis as the limitations of claim 10 are similarly rejected.
Regarding claim 11, see above rejection for claim 9. It is a system claim reciting similar subject matter as claim 3. Please see above claim 3 for detailed claim analysis as the limitations of claim 11 are similarly rejected.
Regarding claim 12, see above rejection for claim 9. It is a system claim reciting similar subject matter as claim 4. Please see above claim 4 for detailed claim analysis as the limitations of claim 12 are similarly rejected.
Regarding claim 13, see above rejection for claim 12. It is a system claim reciting similar subject matter as claim 5. Please see above claim 5 for detailed claim analysis as the limitations of claim 13 are similarly rejected.
Regarding claim 14, see above rejection for claim 9. It is a system claim reciting similar subject matter as claim 6. Please see above claim 6 for detailed claim analysis as the limitations of claim 14 are similarly rejected.
Regarding claim 15, it recites a system performing the method of claim 1. Bhattacharjee, Ono, and Correa teach a system performing the method of claim 1 (see Bhattacharjee [0044]). Please see above for detailed claim analysis, with the exception to the following further limitations:
a graphic processing unit (GPU) configured to generate an image signal encoding image data of a virtual image (see Correa col. 7, ln. 5-40, where the at least one processor includes a GPU and the processor is configured to output display images data);
a surface (see Ono [0028], where a wind shield is projected upon);
a projector configured to project the virtual image on the surface (see Ono [0028]-[0031], where the image light is emitted from the image display device); and
a processor (see Bhattacharjee [0044], where the computing device includes a processor and memory, where the memory stores various data and software for the operations of the computing device)
Please see the above rejection for claim 1, as the rationale to combine the teachings of Bhattacharjee, Ono, and Correa are similar, mutatis mutandis.
Regarding claim 16, see above rejection for claim 15. It is a system claim reciting similar subject matter as claim 2. Please see above claim 2 for detailed claim analysis as the limitations of claim 16 are similarly rejected.
Regarding claim 17, see above rejection for claim 15. It is a system claim reciting similar subject matter as claim 3. Please see above claim 3 for detailed claim analysis as the limitations of claim 17 are similarly rejected.
Regarding claim 18, see above rejection for claim 15. It is a system claim reciting similar subject matter as claim 5. Please see above claim 5 for detailed claim analysis as the limitations of claim 18 are similarly rejected.
Regarding claim 19, see above rejection for claim 15. It is a system claim reciting similar subject matter as claim 6. Please see above claim 6 for detailed claim analysis as the limitations of claim 19 are similarly rejected.
Regarding claim 20,. Bhattacharjee, Ono, and Correa disclose a vehicle comprising the system recited in claim 15 (see Ono [0028], where the HUD is provided in a vehicle).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TIMOTHY WING HO CHOI whose telephone number is (571)270-3814. The examiner can normally be reached 9:00 AM to 5:00 PM.
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/TIMOTHY CHOI/Examiner, Art Unit 2671
/VINCENT RUDOLPH/Supervisory Patent Examiner, Art Unit 2671
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