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 .
This office action is in response to Request for Continued Examination filed on 23 June 2026 and Applicant’s Response After Final filed on 20 May 2026.
This office action is made Non Final.
Claims 1, 3, 4, 12 and 14 have been amended.
Claims 4 have been cancelled.
Claim 15-16 has been added.
All rejections, as presented in the previous office action, have been withdrawn as neccessited by Applicant’s amendment
Claims 1-3, 7-9, 12-16 are pending. Claims 1, 12, and 14 are independent claims.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 6/9/26 has been entered.
Claim Interpretation
The limitations of Claim 14 no longer invoke 35 U.S.C. § 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) in response to Applicant’s amendments.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-3, 7-9 12-14 remain and 15-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation “training the control unit to provide a luminance map with a training dataset of image data”. However, the element “luminance map” was already introduced in the “transforming” limitation in line 4 of claim 1. Therefore, it is unclear if “luminance map” element in the training limitation depends on the element “luminance map” in the transforming limitation or viewed as its own element. In addition, the element “image data” was already introduced in the “transforming” limitation in line 4 of claim 1. It is also unclear if the “image data” element in the training limitation depends on the element “image data” in the transforming limitation or viewed as its own element. Therefore, the claim is vague and indefinite. For examining purposes, the Examiner will view this limitation of claim 1 as “training the control unit to provide the luminance map with a training dataset of the image data.
Claim 12 recites the limitation “training the control unit to provide a luminance map with a training dataset of image data”. However, the element “luminance map” was already introduced in the “transform” limitation in the previous lines of claim 12. Therefore, it is unclear if “luminance map” element in the training limitation depends on the element “luminance map” in the transform limitation or viewed as its own element. In addition, the element “image data” was already introduced in the “transform” limitation in the previous lines of claim 12. It is also unclear if the “image data” element in the training limitation depends on the element “image data” in the transform limitation or viewed as its own element. Therefore, the claim is vague and indefinite. For examining purposes, the Examiner will view this limitation of claim 12 as “training the control unit to provide the luminance map with a training dataset of the image data.
Claim 12 recites the limitation “transform the image data into a luminance map wherein an operation of transforming the image data includes a use of a machine learning algorithm”. However, the element “luminance map” was already introduced in the third limitation of claim 12. Therefore, it is unclear if “luminance map” element in this transform limitation depends on the element “luminance map” in the third limitation of claim 12 or viewed as its own element. In addition, the step “transform the image data” was already introduced in the third limitation. It is also unclear if “transform the image data” or “transforming the image data” of this limitation depends on the “transform the image data” in third limitation or viewed as its own element. Therefore, the claim is vague and indefinite. For examining purposes, the Examiner will view this limitation of claim 12 as “the transform the image data into the luminance map wherein an operation of the transform the image data includes a use of a machine learning algorithm.”
Furthermore, the limitation “wherein transforming the image data into a luminance map is implemented by…” comprises similar issues as the ““transform the image data” limitation and is rejected under similar rationale and interpreted similar to the explained examining purposes above.
Claim 12 recites the limitation “a training operation that provides the luminance map with a training dataset of the image data”. However, the element “training dataset” was already introduced in the third limitation of claim 12. Therefore, it is unclear if “training dataset” element in the training operation limitation depends on the element “training dataset” in the third limitation or viewed as its own element. Therefore, the claim is vague and indefinite. For examining purposes, the Examiner will view this limitation of claim 12 as “a training operation that provides the luminance map with the training dataset of the image data”.
Claim 14 recites the limitation “training the control unit to provide a luminance map with a training dataset of image data”. However, the element “image data” was already introduced in the “transforming” limitation in line 4 of claim 14. It is also unclear if the “image data” element in the training limitation depends on the element “image data” in the transforming limitation or viewed as its own element. Therefore, the claim is vague and indefinite. For examining purposes, the Examiner will view this limitation of claim 1 as “training the control unit to provide the luminance map with a training dataset of the image data.
Any claim not specifically addressed, above, is being rejected as its failure to overcome the incorporated deficiencies of a claim upon which is depends on.
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.
Claim(s) 1-2 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Shibata et al (US20200139879, pub. 5/7/2020) in further view of Fdhal et al (US20130113383, 2013)
As per independent claim 1, Shibata et al discloses a method for operating an automotive lighting device with a matrix arrangement of light pixels, (FIG 1, 2A; 0044: The optical deflection device 26 includes a micro mirror array 32 in which multiple micro mirror elements 30 are arranged in a matrix) the method comprising the steps of:
acquiring image data of a working zone in front of the automotive lighting device; (0035, 0050: imager of the vehicular lamp of the vehicle captures images of an area in front of the vehicle)
transforming the image data into a luminance map; (0051-0052: image data is transmitted to luminance analyzer to create a spatial distribution of light data. Luminance of each region is identified where the collection of region is a form of a map)
wherein transforming the image data into the luminance map is carried out by a control unit which is previously configured to transform the image data into the luminance map by: training the control unit to provide a luminance map with a training dataset of image data; (Note: the term/phrase “previously configured” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “previously configured” is/means. Therefore, the broadest reasonable interpretation is applied. In addition, the term/phrase “training the control unit” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “training the control unit” is/means. Therefore, broadest reasonable interpretation is applied; thus, training can be merely viewed as programming the control unit. 0046,0056,0070 of Shibata detects the luminance of each individual region R is detected every 0.1 to 5 ms, and the luminance of the individual region R is associated with pedestrians, etc along with defining luminance range L 1 - L 3. Furthermore, Shibata discloses provide a luminance map with a training dataset of image data through the detection of luminance value of each individual region R such as 0052-0054. Furthermore, 0051-0052 discloses a control unit, having a luminance analyzer, which carries out the step of determining the luminance of the image data (transforming the image data into a luminance map) and provide a luminance map with a training dataset of image data through the detection of luminance value of each individual region R. Thus, the control unit, through the luminance analyzer, carries out these steps. Therefore, one of a skilled artisan would have realized that the control unit has these instructions implemented/programmed to perform the functionality of transforming the image data into the luminance map and provide luminance map with a training dataset of image data as explained. In addition, the Examiner respectfully states if Shibata’s control unit can perform the functions of transforming the image data… and providing the luminance map.., then the control unit was previously configured to perform these explicit functions )
providing a desired light pattern (0053: The lamp controller 18 sets/provides an illuminance value of light emitted to each individual region R)
calculating an adapted light pattern which provides the desired light pattern when projected over the luminance map; (FIG 5A; 0053-0057, 0082, 0074, 0218; Claim 1:; Based on the detection result from the luminance analyzer 14, the illuminance setting unit 42 determines the illuminance value of light emitted to each individual region R.; the illuminance setting unit 42 produces a predetermined light distribution pattern based on the relationships between the detected luminance value and the set illuminance value shown)
projecting the adapted light pattern (0047-0049, 0065 0081: the adapted lighted pattern produced is projected)
Furthermore, as explained above, Shibata discloses wherein transforming the image data is carried out by a control unit which is previously configured to transform the image data into the luminance map by: training the control unit to provide a luminance map with a training dataset of image data. In addition, as explained above, Shibata discloses detecting luminance value of each individual region R; however, the cited art fails to specifically discloses a testing operation comparing the luminance map with measured luminance map/ testing the control unit comparing the luminance map provided by the control unit with measured luminance map. However, Fdhal discloses a processor (control unit) to compare measured luminance map(s) 28 to desired luminance map(s) 34 (0027) Thus, one of a skilled artisan would have realized that the processor/control unit has these instructions implemented/programmed to perform the functionality of testing/comparing. In addition, the Examiner respectfully states if the processor can perform the functions of testing/comparing, then the processor is previously configured to perform these explicit function(s).
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Fdhal et al since it would have provided the benefit of improve illumination uniformity across viewing area. (0027)
As per dependent claim 2, Shibata et al discloses the method is performed within a rate of between 0 to 2 seconds. (0047, 0065: Discloses occurring every 0.1-5ms, a rate between 0 to 2 seconds)
As per dependent claim 9, Shibata et al discloses the image data is acquired by an infrared camera (0148)
Claim(s) 3 is rejected under 35 U.S.C. 103 as being unpatentable over Shibata et al in further view of Fdhal et al in further view of Sunkavalli et al (US20190164261, 2019)
As per dependent claim 3, Claim 3 recites similar limitations as in Claim 1 and is rejected under similar rationale. In addition, as explained in claim 1, Shibata discloses training the control unit to provide a luminance map with a training dataset of image data. Also, while Shibata discloses the use of machine learning algorithms (0068, 0153), Shibata does not disclose the luminance analyzer/control, that was trained, using a machine learning algorithm to transform the captured image into a spatial distribution of light data. In other words, Shibata does not disclose training the control unit to provide the luminance map includes a use of a machine learning algorithm. Sunkavalli et al discloses training a neural network to generate a reference light intensity map using training data. (0033) The reference light intensity map with training light intensity maps are used to train the neural network system to synthesize light intensity maps for input images (0011, 0062; 0088, FIG 10) Thus after trained, Sunkavalli et al discloses obtaining an image from a camera device and inputting the obtained image into a trained neural network to generate a light intensity map. The light intensity map for the input image indicates the estimated intensity of light emanating from each pixel within a panoramic environment. (0094-0095) Thus, the light intensity map is viewed as a luminance map. Thus, Sunkavalli et al discloses training the control unit to provide the luminance map includes a use of a machine learning algorithm.
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Sunkavalli et al since it would have provided the benefit of providing accurate or robust methods for estimating illumination intensity of a panoramic environment for a single image. (0004)
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Shibata et al in further view of Fdhal et al in further view of Darrer et al (US20210041539, EFD 8/7/2019)
As per dependent claim 7, Shibata et al discloses identifying the position of other objects in the working zone (FIG 3; 0121-0122, 0151) However, the cited art fails to disclose wherein the luminance map isolates the position of the road from the position of other objects in the working zone. However, Darrier et al discloses a luminance image (form of a map) that distinguish the different luminance intensities levels. These different levels indicate the luminance refer to either the headlights of oncoming vehicles or markings of the road. Furthermore, the image indicates which lane the vehicle is traveling and which lane other vehicles are traveling. In particular, the image shows the center dotted line to the left and the solid line to right of the lane the vehicle is traveling. The images show the other lane which the other traveling vehicles are in; solid white lane to the far left and center dotted lane to right of the (FIG. 3, 0046) Thus, Darrier shows the isolation/distinguishing of the isolating the position of the road from the position of other objects in the working zone
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Darrier et al since it would have provided the intrinsic advantage of a simple and efficient method of identifying various objects on the road based on their luminance.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Shibata et al in further view of Fdhal et al in further view of Wood (US20150007217, 2015)
As per dependent claim 8, the cited art fails to specifically disclose the image data includes RGB data. However, Wood discloses the image data includes RGB data (0039)
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Wood et al since the RGB image data has color information that allows the intrinsic advantage of a clearer and more realistic view of the scene
Claim(s) 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Shibata et in further view of Sunkavalli et al in further view of Fdhal et al
As per independent claim 12, Shibata et al discloses a system comprising:
matrix arrangement of solid-state light sources (0043-0044, 0047: multiple micro mirrors arranged in an array (a matrix) for reflecting light from a light source);
a camera configured to acquire image data (0035, 0050)
automotive lighting device…that stores a computer program and that instructs the automotive lighting device to perform a number of functions, (FIG 1, 2A; 0044: The optical deflection device 26 includes a micro mirror array 32 in which multiple micro mirror elements 30 are arranged in a matrix) performing the operations of:
acquire an image data of a working zone from the camera; (0035, 0050: imager (camera) of the vehicular lamp of the vehicle captures images of an area in front of the vehicle)
transforming the image data into a luminance map; (0051-0052: image data is transmitted to luminance analyzer to create a spatial distribution of light data. Luminance of each region is identified where the collection of region is a form of a map)
…wherein transforming the image data into a luminance map is implemented by a training operation that provides a luminance map with a training dataset of image data; (0046,0056,0070 detects the luminance of each individual region R is detected every 0.1 to 5 ms, and the luminance of the individual region R is associated with pedestrians, etc along with defining luminance range L 1 - L 3. Furthermore, Shibata discloses provide a luminance map with a training dataset of image data through the detection of luminance value of each individual region R such as 0052-0054))
provide a desired light pattern (0053: The lamp controller 18 sets/provides an illuminance value of light emitted to each individual region R)
calculate an adapted light pattern which provides the desired light pattern when projected over the luminance map; (FIG 5A; 0053-0057, 0082, 0074, 0218; Claim 1:; Based on the detection result from the luminance analyzer 14, the illuminance setting unit 42 determines the illuminance value of light emitted to each individual region R.; the illuminance setting unit 42 produces a predetermined light distribution pattern based on the relationships between the detected luminance value and the set illuminance value shown)
project the adapted light pattern with the matrix arrangement of solid-state light sources (FIG 2, 4; 0043-0044, 0047-0049, 0065 0081: the adapted lighted pattern produced is projected)
While Shibata discloses the use of machine learning algorithms (0068, 0153), Shibata does not disclose the luminance analyzer using a machine learning algorithm to transform the captured image into a spatial distribution of light data. In other words, Shibata does not disclose wherein an operation of transforming the image data includes a use of a machine learning algorithm. However, Sunkavalli et al discloses obtaining an image from a camera device and inputting the obtained image into a neutral network to generating a light intensity map. The light intensity map for the input image indicates the estimated intensity of light emanating from each pixel within a panoramic environment. (0051-0052) Thus, the light intensity map is viewed as a luminance map. In addition, a neutral network is a machine learning algorithm (see 0005)
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Sunkavalli et al since it would have provided the benefit of providing accurate or robust methods for estimating illumination intensity of a panoramic environment for a single image. (0004)
In addition, Shibata et al discloses a control unit that performs the transforming the image data into a luminance map (0051-0052 discloses a control unit, having a luminance analyzer which determines the luminance of the image data. Thus, the control unit, through the luminance analyzer, carries out these steps.) which is previously configured to transform the image data into a luminance map by training the control unit to provide a luminance map with a training dataset of image data; (see 0046,0056,0070 as explain above which explains Shibata discloses provide a luminance map with a training dataset of image data through the detection of luminance value of each individual region R such as 0052-0054 through the luminance analyzer/control unit. Therefore, one of a skilled artisan would have realized that the control unit has these instructions implemented/programmed to perform the functionality of transforming the image data into the luminance map and provide luminance map with a training dataset of image data as explained. In addition, the Examiner respectfully states if Shibata’s control unit can perform the functions of transforming the image data… and providing the luminance map.., then the control unit was previously configured to perform these explicit functions)
Furthermore, as explained above, Shibata discloses detecting luminance value of each individual region R; however, the cited art fails to specifically discloses a testing operation comparing the luminance map with measured luminance map/ testing the control unit comparing the luminance map provided by the control unit with measured luminance map. However, Fdhal discloses a processor (control unit) to compare measured luminance map(s) 28 to desired luminance map(s) 34 (0027) Thus, one of a skilled artisan would have realized that the processor/control unit has instructions implemented/programmed to perform the functionality of testing/comparing. In addition, the Examiner respectfully states if the processor/control unit can perform the functions of testing/comparing, then the processor/control unit is previously configured to perform these explicit function(s).
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Fdhal et al since it would have provided the benefit of improve illumination uniformity across viewing area. (0027)
As per dependent claim 13, wherein the matrix arrangement includes at least 2000 solid-state light sources (FIG 2A; 0047)
Claim(s) 14, 16 are rejected under 35 U.S.C. 103 as being unpatentable over Shibata et al in further view of Fdhal et al in further view of Takai et al (US20210162927, 2013)
As per independent claim 14, Shibata et al discloses a method for operating an automotive lighting device with a matrix arrangement of light pixels, (FIG 1, 2A; 0044: The optical deflection device 26 includes a micro mirror array 32 in which multiple micro mirror elements 30 are arranged in a matrix) the method comprising the steps of:
acquiring image data of a working zone in front of the automotive lighting device; (0035, 0050: imager of the vehicular lamp of the vehicle captures images of an area in front of the vehicle)
transforming the image data into a luminance map; (0051-0052: image data is transmitted to luminance analyzer to create a spatial distribution of light data. Luminance of each region is identified where the collection of region is a form of a map)
wherein transforming the image data is carried out by a control unit which is previously configured to transform the image data into the luminance map by: training the control unit to provide a luminance map with a training dataset of image data; (Note: the term/phrase “previously configured” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “previously configured” is/means. Therefore, broadest reasonable interpretation is applied. In addition, the term/phrase “training the control unit” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “training the control unit” is/means. Therefore, broadest reasonable interpretation is applied. Thus, training is merely viewed as programming the control unit. 0046,0056,0070 of Shibata detects the luminance of each individual region R is detected every 0.1 to 5 ms, and the luminance of the individual region R is associated with pedestrians, etc along with defining luminance range L 1 - L 3. Furthermore, Shibata discloses provide a luminance map with a training dataset of image data through the detection of luminance value of each individual region R such as 0052-0054. Furthermore, 0051-0052 discloses a control unit, having a luminance analyzer, which carries out the step of determining the luminance of the image data (transforming the image data into a luminance map) and provide a luminance map with a training dataset of image data through the detection of luminance value of each individual region R. Therefore, the control unit, through the luminance analyzer, carries out these steps. Thus, one of a skilled artisan would have realized that the control unit has instructions implemented/programmed to perform the functionality of transforming the image data into the luminance map and provide luminance map with a training dataset of image data. In addition, the Examiner respectfully states if the control unit can perform the functions of transforming the image data… and providing the luminance map.., then the control unit is previously configured to perform these explicit functions )
providing a desired light pattern (0053: The lamp controller 18 sets/provides an illuminance value of light emitted to each individual region R)
calculating an adapted light pattern which provides the desired light pattern when projected over the luminance map; (FIG 5A; 0053-0057, 0082, 0074, 0218; Claim 1:; Based on the detection result from the luminance analyzer 14, the illuminance setting unit 42 determines the illuminance value of light emitted to each individual region R.; the illuminance setting unit 42 produces a predetermined light distribution pattern based on the relationships between the detected luminance value and the set illuminance value shown)
wherein the calculating the adapted light pattern is carried out by the control unit, which is previously configured to calculate the adapted light pattern by: training the control unit toto calculate an adapted light pattern in response to a training dataset of luminance map and desired light pattern (FIG 5A; 0053-0057, 0082, 0074, 0218; Claim 1: set illuminance value for each luminance range L1-L3; 0027: the light source unit 10 changes the light distribution pattern every 0.1 to 5 ms, so the detected luminance value of each individual region R measured after the change can be said to be a light pattern. Furthermore, 0053 discloses illuminance value provided/carried/calculated by the illuminance setting unit 42 of control device 50 (FIG 1)); thus a control unit, through the illuminance setting unit, is performing the calculating. the control unit, through the luminance analyzer carries out these steps. Thus, one of a skilled artisan would have realized that the control unit has instructions implemented/programmed to perform the functionality of calculating the adapted light pattern and calculate an adapted light pattern in response to a training dataset of luminance map and desired light pattern. In addition, the Examiner respectfully states if the control unit can perform the functions of both calculating steps, then the control unit is previously configured to perform these explicit functions)
projecting the adapted light pattern (0047-0049, 0065 0081: the adapted lighted pattern produced is projected)
Furthermore, as explained above, Shibata discloses wherein transforming the image data is carried out by a control unit which is previously configured to transform the image data into the luminance map by: training the control unit to provide a luminance map with a training dataset of image data. In addition, as explained above, Shibata discloses detecting luminance value of each individual region R; however, the cited art fails to specifically discloses a testing operation comparing the luminance map with a measured luminance map/ testing the control unit comparing the luminance map provided by the control unit with measured luminance map. However, Fdhal discloses a processor (control unit) to compare measured luminance map(s) 28 to desired luminance map(s) 34 (0027) Thus, one of a skilled artisan would have realized that the processor/control unit has instructions implemented/programmed to perform the functionality of testing/comparing. In addition, the Examiner respectfully states if the processor/control unit can perform the functions of testing/comparing, then the processor/control unit is previously configured to perform these explicit function(s).
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Fdhal et al since it would have provided the benefit of improve illumination uniformity across viewing area. (0027)
Furthermore, as explained above, Shibata teaches wherein the calculating the adapted light pattern is carried out by a control unit by training the control unit to calculate the adapted light pattern in response to a training dataset of the luminance map and the desired light pattern. However, the cited art fails to specifically disclose testing the control unit comparing the adapted light pattern that is calculated with measured light pattern. However, Takai et al disclose compares a light pattern of a captured image with a reference light pattern (0042, 0147, 0152, 0160) 0152 discloses a control unit doing the comparing. Thus, one of a skilled artisan would have realized that the control unit has instructions implemented/programmed to perform the functionality testing/comparing. In addition, the Examiner respectfully states if the processor can perform the functions of testing/comparing, then the processor is previously configured to perform these explicit function(s).
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Takai et al since it would have provided the benefit that allows an occupant to accurately recognize visual communication between a vehicle and an object. (0007)
As per dependent claim 16, Shibata et al discloses the image data is acquired by an infrared camera (0148)
Claim(s) 15 is rejected under 35 U.S.C. 103 as being unpatentable over Shibata et al et al in further view of Fdhal et al further view of Takai et al in further view of Ando (US20210289604, EFD 2016)
As per dependent claim 15, while Shibata discloses the use of machine learning algorithms (0068, 0153), the cited art does not disclose illuminance setting unit using a machine learning algorithm to calculate an adapted light pattern. In other words, the cited fails to specifically disclose the training the control unit calculate the adapted light pattern includes use of the machine learning algorithm. However, Ando discloses training the control unit to calculate the adapted light pattern includes use of the machine learning algorithm (0013: calculating, using a neural network, illumination pattern information for generating an illumination pattern. Furthermore, Ando discloses the neural network is trained using learning data containing the state information illumination pattern data corresponding to the state information. (0007, 0058-0059) Thus, Ando discloses training the neural network to calculate the adapted light pattern.
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Ando since it would have provided the benefit of calculating an optimal illumination pattern even when the illumination target changes in a complex manner. (0006)
Response to Arguments
Applicant's arguments filed 5/20/26 have been fully considered but they are not persuasive.
On pages 6-7, in regards to the 35 USC 112 rejection(s), Applicant’s amendment has overcome the pending issues in Claim 14 that were disclosed in the previous office action. However, the amendments made to the claims comprises new issue(s) within the claims that were not previously presented. The Examiner respectfully points to the Applicant to the “Claim Rejections - 35 USC § 112” section of the office action above regarding the matter. Therefore, the 112 rejection(s) to the claim 14 remain.
On pages 8-11, in regards to amended claim 1, Applicant argues the cited art, Shibata and Fadhl do not teach the subject matter: transforming the image data into a luminance map "is carried out by a control unit which is previously configured to transform the image data into the luminance map by: training the control unit to provide a luminance map with a training dataset of image data, and testing the control unit comparing the luminance map provided by the control unit with a measured luminance map." Applicant argues explicitly that the amended limitations requires that the control unit undergo a prior training process - completed before the method is performed - in which the control unit is trained using a training dataset and then tested by comparing its output luminance map against a measured luminance map. Particularly, Applicant argues that Shibata does not teach the subject matter because Shibata's luminance analyzer performs a continuous, real-time detection of luminance values from image data acquired by the imager during vehicle operation. In other words, Applicant argues that Shibata’s detection of luminance values from image data is an operational feedback loop performed during use of the vehicular lamp - it is not a prior training process performed before installation that discloses no training dataset of image data used to train a control unit, no testing step in which the control unit's output luminance map is compared against a measured luminance map, and no prior configuration of the control unit through any training process. Furthermore, Applicant argues that Fdhal does not teach the subject matter because Fadhl discloses an apparatus for improving illumination uniformity of a light booth viewing area, in which a processor compares measured luminance maps to desired luminance maps and outputs luminance adjustment maps to cause adjustment light sources to attenuate non-uniformities. Applicant argues that Fdhal discloses a real-time feedback control loop for correcting illumination uniformity in a static viewing environment - it is not a testing step in a prior training process for a control unit. Thus, Applicant argues that Shibata and Fdhal contains no teaching of a control unit that has been previously configured through a prior training and testing process before installation. However, the Examiner disagrees.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., control unit undergo a prior training process - completed before the method is performed; not a prior training process performed before installation; teaching of a control unit that has been previously configured through a prior training and testing process before installation) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Based on the language of the argued limitations, the subject matter/limitations “carried out by a control unit which is previously configured to transform the image data into the luminance map by: training the control unit to provide a luminance map with a training dataset of image data, and testing the control unit comparing the luminance map provided by the control unit with a measured luminance map." do not state the control unit undergoes any prior training process before any installation or previously configured through a prior training and testing process before installation. The Examiner respectfully states the claim as a whole does not mention the term/word “installation” at all. Furthermore, the language collectively does not explicitly disclose any prior training in any way being done, especially before any installation. In other words, the language is completely silent that a control unit is trained before any installation. In regards to the language, “carried out by a control unit which is previously configured”, the language is silent and/or broad on a number of elements. The claimed language does not clarify or explained on how a control unit is “previously configured” to perform the test the training and testing steps. The language provides no additional limitations on how the control unit is actually previously configured. In other words, the term/phrase “previously configured” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “previously configured” is/means. Therefore, the broadest reasonable interpretation is applied. Therefore, control units are known to be configured with instructions to perform said functionalities such as the training and testing steps. Therefore, control units that perform a function are therefore “previously configured” to perform said function. In addition, the language “training the control unit to provide a luminance map with a training dataset of image data” is silent and/or broad on a number of elements. The claimed language does not clarify or explain how exactly the control unit is trained. The term/phrase “training the control unit” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “training the control unit” is/means. In other words, no additional language is provided on how to interpret “training the control unit”. Furthermore, the language does not clarify or explained what “training dataset” actually is. The language only states a luminance map is provided with a training dataset of image data. The language provides no additional data on what exactly the training dataset is, how the control unit is especially trained out and what is outputted. The language only states that the luminance map is provided with data. The language does not disclose in any way the control unit is a machine learning model that receives training data to train it. Therefore, the broadest reasonable interpretation is applied. Furthermore, the language “testing the control unit comparing the luminance map provided by the control unit with a measured luminance map” is silent and/or broad on a number of elements. The language does not clarify or explained how exactly the control unit is tested. In addition, the language does not explicitly disclose how the maps are compared. Therefore, the broadest reasonable interpretation is applied. Based on the language, it appears testing the control unit is merely the control unit comparing the luminance map with a measured luminance map. In other words, the language is not claiming any testing being performed but merely stating that the control unit is comparing two maps.
Furthermore, the Examiner refers the Applicant to MPEP 904.01 (b) that states "All subject matter that is the equivalent of the subject matter as defined in the claim, even though specifically different from the definition in the claim, must be considered unless expressly excluded by the claimed subject matter." In other words, while the prior art cited may not explicitly use the same terminology as disclosed in the claim limitations, it doesn't mean the art doesn't teach it and can't be considered to reject Applicant’s claimed invention. Thus, examiner submits that what is taught by the references of the cited art is considered functionally equivalent to that which is claimed discussed below.
Therefore, based on the broadest reasonable interpretation of language of the subject matter/limitations, Shibata discloses the subject matter of transforming the image data into a luminance map. 0051-0052 of Shibata discloses image data is transmitted to luminance analyzer to create a spatial distribution of light data. Luminance of each region is identified where the collection of region is a form of a map. Furthermore, Shibata teaches the subject matter of wherein transforming the image data is carried out by a control unit which is previously configured to transform the image data into the luminance map by: training the control unit to provide a luminance map with a training dataset of image data. As explained above, the term/phrase “previously configured” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “previously configured” is/means. Therefore, the broadest reasonable interpretation is applied. In addition, the term/phrase “training the control unit” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “training the control unit” is/means. Therefore, broadest reasonable interpretation is applied; thus, training can be merely viewed as programming the control unit. Thus, 0046,0056,0070 of Shibata detects the luminance of each individual region R is detected every 0.1 to 5 ms, and the luminance of the individual region R is associated with pedestrians, etc along with defining luminance range L 1 - L 3. Furthermore, Shibata discloses provide a luminance map with a training dataset of image data through the detection of luminance value of each individual region R such as 0052-0054. Furthermore, 0051-0052 discloses a control unit, having a luminance analyzer, which carries out the step of determining the luminance of the image data (transforming the image data into a luminance map) and provide a luminance map with a training dataset of image data through the detection of luminance value of each individual region R. Thus, the control unit, through the luminance analyzer, carries out these steps. Therefore, one of a skilled artisan would have realized that the control unit has these instructions implemented/programmed to perform the functionality of transforming the image data into the luminance map and provide luminance map with a training dataset of image data as explained. In addition, the Examiner respectfully states if Shibata’s control unit can perform the functions of transforming the image data… and providing the luminance map.., then the control unit was previously configured to perform these explicit functions.
Furthermore, as explained above, Shibata discloses wherein transforming the image data is carried out by a control unit which is previously configured to transform the image data into the luminance map by: training the control unit to provide a luminance map with a training dataset of image data. In addition, as explained above, Shibata discloses detecting luminance value of each individual region R; however, the cited art fails to specifically discloses a testing operation comparing the luminance map with measured luminance map/ testing the control unit comparing the luminance map provided by the control unit with measured luminance map. However, Fdhal discloses a processor (control unit) to compare measured luminance map(s) 28 to desired luminance map(s) 34 (0027) Thus, one of a skilled artisan would have realized that the processor/control unit has these instructions implemented/programmed to perform the functionality of testing/comparing. In addition, the Examiner respectfully states if the processor can perform the functions of testing/comparing, then the processor is previously configured to perform these explicit function(s).
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Fdhal et al since it would have provided the benefit of improve illumination uniformity across viewing area. (0027)
Therefore, the cited art teaches the argued limitation.
On page 10, Applicant argues that “a person of ordinary skill in the art would have had no reason to combine Shibata's real-time luminance detection system with Fdhal's light booth uniformity correction apparatus to arrive at the claimed prior training framework. Shibata is directed to a vehicular lamp system that dynamically adjusts illuminance during vehicle operation. Fdhal is directed to improving illumination uniformity in a static photographic viewing booth. The two systems operate in fundamentally different environments, address fundamentally different problems, and employ fundamentally different operational architectures. However, the Examiner disagrees.
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, Furthermore, all references are combinable since they share a similar field of endeavor and/or features. Shibata discloses detecting luminance values from image data in order to create a spatial distribution of light data. Luminance of each region is identified where the collection of region is a form of a map. (0051-0052) Fdhal discloses the subject matter of sensing luminance map(s) which luminance values may be derived from captured images to produce measured luminance map(s). Measured luminance map(s) 28 may comprise an array of luminance values representative of the illumination intensity of corresponding regions of viewing area(s) 14. For example, measured luminance map(s) 28 may comprise an array of numeric luminance (e.g. brightness) values associated with corresponding individual pixels or groups of pixels captured by camera(s) 22, 220 (0030-0031) The measured luminance maps are then compared with to desired luminance map(s) (0027). Thus, both Shibata and Fdhal both disclose the subject matter of detecting luminance values from image data in order to create a spatial distribution of light data/luminance maps. Thus, as explained by the Examiner, the cited references share similar functionalities and a shared common field of endeavor resulting in the cited art being combinable., In addition, the Examiner respectfully states "the teachings relied upon were repeated in a number of references further strengthens the conclusion of obviousness." Kansas Jack, Inc. v. Kuhn, 719 F.2d 1144, 1150 (Fed. Cir. 1983). In addition, the motivation used for the combination of Bernstein with Kim and Fenton was found Bernstein itself and meets the requirements of 35 USC 103 and established case law as stated above. Thus, the Examiner has provided rational underpinning to support the conclusion of obviousness as required under KSR.
Furthermore, the Examiner is not combining whole inventions by brute force
when the Examiner stated the obvious statement in combining Shibata with Fdhal. The Examiner is modifying Shibata with the feature of Fdhal since Fdhal discloses a processor (control unit) to compare measured luminance map(s) to desired luminance map(s) 34 (0027) Shibata discloses generating luminance maps but does not compare these generated maps with other luminance maps. Thus, Fdhal’s comparing of luminance maps would add another feature to Shibata that Shibata lacked Thus, Shibata is being modified by the disclosed features of Fdhal and not the entire invention of Fdhal. Thus, the test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).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).
On pages 11-12, in regards to claim 14, the Applicant argues that the cited art, does not teach the subject matter: "is carried out by the control unit, which is previously configured to calculate the adapted light pattern by: training the control unit to calculate the adapted light pattern in response to a training dataset of the luminance map and the desired light pattern; and testing the control unit by comparing the calculated adapted light pattern with a measured light pattern." Applicant argues explicitly that the amended limitations requires a prior training process - in which the control unit is trained and tested specifically for the adapted light pattern calculation before installation. Particularly, Applicant argues Takai discloses a vehicle display system in which a determination unit calculates a ratio of change of a light pattern of a captured image to a reference light pattern, for the purpose of determining whether a projected road-surface light pattern has been changed due to an object such as a pedestrian. This comparison is performed during vehicle operation to detect the presence of objects - it is not a testing step in a prior training process for a control unit. Takai discloses no training dataset of luminance maps and desired light patterns, no control unit being trained to calculate an adapted light pattern, and no prior configuration of any control unit through a training and testing process. Thus, Applicant argues that Takai contains no teaching of a control unit that has been previously configured through a prior training and testing process before installation. However, the Examiner disagrees.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., a prior training process - in which the control unit is trained and tested specifically for the adapted light pattern calculation before installation) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Based on the language of the argued limitations, the subject matter/limitations “is carried out by the control unit, which is previously configured to calculate the adapted light pattern by: training the control unit to calculate the adapted light pattern in response to a training dataset of the luminance map and the desired light pattern; and testing the control unit by comparing the calculated adapted light pattern with a measured light pattern" do not state the control unit undergoes any prior training process before any installation or previously configured through a prior training and testing process before installation. The Examiner respectfully states the claim as a whole does not mention the term/word “installation” at all. Furthermore, the language collectively does not explicitly disclose any prior training in any way being done, especially before any installation. In other words, the language is completely silent that a control unit is trained before any installation. In regards to the language, “carried out by a control unit which is previously configured”, the language is silent and/or broad on a number of elements. The claimed language does not clarify or explained on how a control unit is “previously configured” to perform the test the training and testing steps. The language provides no additional limitations on how the control unit is actually previously configured. In other words, the term/phrase “previously configured” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “previously configured” is/means. Therefore, the broadest reasonable interpretation is applied. Therefore, control units are known to be configured with instructions to perform said functionalities such as the training and testing steps. Therefore, control units that perform a function are therefore “previously configured” to perform said function. In addition, the language “training the control unit to calculate the adapted light pattern in response to a training dataset of the luminance map and the desired light pattern” is silent and/or broad on a number of elements. The claimed language does not clarify or explain how exactly the control unit is trained. The term/phrase “training the control unit” is not defined by the claim language and the specification does not provide an explicit definition of what of the term/phrase “training the control unit” is/means. In other words, no additional language is provided on how to interpret “training the control unit”. Furthermore, the language does not clarify or explained what “training dataset” actually is. The language only states a luminance map is provided with a training dataset of image data. The language provides no additional data on what exactly the training dataset is, how the control unit is especially trained out and what is outputted. The language only states that the luminance map is provided with data. The language does not disclose in any way the control unit is a machine learning model that receives training data to train it. Therefore, the broadest reasonable interpretation is applied. Furthermore, the language “testing the control unit by comparing the calculated adapted light pattern with a measured light pattern” is silent and/or broad on a number of elements. The language does not clarify or explained how exactly the control unit is tested. In addition, the language does not explicitly disclose how the patterns are compared. Therefore, the broadest reasonable interpretation is applied. Based on the language, it appears testing the control unit is merely the control unit comparing the calculated adapted light pattern with a measured light pattern. In other words, the language is not claiming any testing being performed but merely stating that the control unit is comparing two patterns.
Furthermore, the Examiner refers the Applicant to MPEP 904.01 (b) that states "All subject matter that is the equivalent of the subject matter as defined in the claim, even though specifically different from the definition in the claim, must be considered unless expressly excluded by the claimed subject matter." In other words, while the prior art cited may not explicitly use the same terminology as disclosed in the claim limitations, it doesn't mean the art doesn't teach it and can't be considered to reject Applicant’s claimed invention. Thus, examiner submits that what is taught by the references of the cited art is considered functionally equivalent to that which is claimed discussed below.
Therefore, based on the broadest reasonable interpretation of language of the subject matter/limitations, Shibata discloses the subject matter of calculating an adapted light pattern which provides the desired light pattern when projected over the luminance map. FIG 5A; 0053-0057, 0082, 0074, 0218; Claim 1 of Shibata discloses based on the detection result from the luminance analyzer 14, the illuminance setting unit 42 determines the illuminance value of light emitted to each individual region R.; the illuminance setting unit 42 produces a predetermined light distribution pattern based on the relationships between the detected luminance value and the set illuminance value shown) Furthermore, Shibata discloses the subject matter of wherein the calculating the adapted light pattern is carried out by the control unit, which is previously configured to calculate the adapted light pattern by: training the control unit toto calculate an adapted light pattern in response to a training dataset of luminance map and desired light pattern. FIG 5A; 0053-0057, 0082, 0074, 0218; Claim 1 of Shitbata discloses set illuminance value for each luminance range L1-L3; 0027: the light source unit 10 changes the light distribution pattern every 0.1 to 5 ms, so the detected luminance value of each individual region R measured after the change can be said to be a light pattern. Furthermore, 0053 discloses illuminance value provided/carried/calculated by the illuminance setting unit 42 of control device 50 (FIG 1)); thus a control unit, through the illuminance setting unit, is performing the calculating. the control unit, through the luminance analyzer carries out these steps. Thus, one of a skilled artisan would have realized that the control unit has instructions implemented/programmed to perform the functionality of calculating the adapted light pattern and calculate an adapted light pattern in response to a training dataset of luminance map and desired light pattern. In addition, the Examiner respectfully states if the control unit can perform the functions of both calculating steps, then the control unit is previously configured to perform these explicit functions. Furhtermore, Shibata discloses the subject matter of projecting the adapted light pattern. 0047-0049, 0065 0081 of Shibata discloses the adapted lighted pattern produced is projected.
Furthermore, as explained above, Shibata teaches wherein the calculating the adapted light pattern is carried out by a control unit by training the control unit to calculate the adapted light pattern in response to a training dataset of the luminance map and the desired light pattern However, the cited art fails to specifically disclose testing the control unit comparing the adapted light pattern that is calculated with measured light pattern. However, Takai et al disclose compares a light pattern of a captured image with a reference light pattern (0042, 0147, 0152, 0160) 0152 discloses a control unit doing the comparing. Thus, one of a skilled artisan would have realized that the control unit has instructions implemented/programmed to perform the functionality testing/comparing. In addition, the Examiner respectfully states if the processor can perform the functions of testing/comparing, then the processor is previously configured to perform these explicit function(s).
It would have been obvious to one of ordinary skill in the before the effective filing date to have modified the cited art with the cited disclosed features of Takai et al since it would have provided the benefit that allows an occupant to accurately recognize visual communication between a vehicle and an object. (0007)
Therefore, the cited art teaches the argued limitation.
On page 12, Applicant argues that “Examiner's stated motivation for combining Takai - that it "would have provided the benefit that allows an occupant to accurately recognize visual communication between a vehicle and an object" - is entirely unrelated to the problem addressed by the claimed invention, which is the prior configuration of a control unit to calculate an optimal adapted light pattern. A person of ordinary skill in the art would have had no reason to apply Takai's road-surface light pattern change detection system to arrive at a
control unit previously trained and tested for adapted light pattern calculation.” However, the Examiner disagrees.
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, Furthermore, all references are combinable since they share a similar field of endeavor and/or features. Shibata discloses the illuminance setting unit produces a predetermined light distribution pattern based on the relationships between the detected luminance value and the set illuminance value shown. (FIG 5A; 0053-0057, 0082, 0074, 0218; Claim 1) Takai discloses the subject matter of acquires captured image information of the light pattern captured by the camera 6 from the vehicle control unit 3 and determines whether the light pattern is changed due to the object based on the captured image information of the light pattern. Takai discloses acquires the reference light pattern from the memory and compares the shape of the light pattern of the captured image captured by the camera 6 with the shape of the reference light pattern. ((0042, 0147, 0152, 0160) Thus, both Shibata and Taki both disclose the subject matter of capturing and detecting light patterns from image data. Thus, as explained by the Examiner, the cited references share similar functionalities and a shared common field of endeavor resulting in the cited art being combinable. In addition, the Examiner respectfully states "the teachings relied upon were repeated in a number of references further strengthens the conclusion of obviousness." Kansas Jack, Inc. v. Kuhn, 719 F.2d 1144, 1150 (Fed. Cir. 1983). In addition, the motivation used for the combination of Takai with Shibata was found Takai itself and meets the requirements of 35 USC 103 and established case law as stated above. Thus, the Examiner has provided rational underpinning to support the conclusion of obviousness as required under KSR.
Furthermore, the Examiner is not combining whole inventions by brute force
when the Examiner stated the obvious statement in combining Shibata with Takai. The Examiner is modifying Shibata with the feature of Takai since Takai discloses compares a light pattern of a captured image with a reference light pattern (0042, 0147, 0152, 0160) 0152 discloses a control unit doing the comparing. Shibata discloses calculating adapt light patterns but does not compare these generated light patterns with other light patterns. Thus, Takai’s comparing of light patterns would add another feature to Shibata that Shibata lacked Thus, Shibata is being modified by the disclosed features of Takai and not the entire invention of Takai. Thus, the test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).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).
Therefore, the cited art teaches the claim.
On pages 13-14, in regards to independent claim 12, Applicant argues substantially similar arguments presented above why the cited art doesn’t teach the limitations for claim 1. As noted above, the Examiner respectfully disagrees with Applicant’s arguments, and the rationale and/or Examiner's explanation to the arguments in regards to Claim 1, disclosed above, is used to respond to the similar arguments for Claim 12.
Conclusion
If the Applicant chooses to amend the claims in future filings, the Examiner kindly states any new limitation(s) added to the claims must be described in the specification in such a way as to reasonably convey to one skilled in the relevant art in order to meet the written description requirement of 35 USC 112, first paragraph. To help expedite prosecution, promote compact prosecution and prevent a possible 112(a)/first paragraph rejection, the Examiner respectfully requests for each new limitation added to the claims in a future filing by the Applicant that the Applicant would cite the location within the specification showing support for that new limitation within the remarks. In addition, MPEP 2163.04(I)(B) states that a prima facie under 112(a)/first paragraph may be established if a claim has been added or amended, the support for the added limitation is not apparent, and applicant has not pointed out where added the limitation is supported.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID FABER whose telephone number is (571)272-2751. The examiner can normally be reached Monday - Thursday.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Adam Queler can be reached at 5712724140. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ADAM M QUELER/ Supervisory Patent Examiner, Art Unit 2172
/D.F/ Examiner, Art Unit 2172
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