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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 8 April 2026 has been entered.
Response to Arguments
Applicant’s arguments, see Response to Final Office Action mailed 2 February 2026, filed 23 March 2026, with respect to the rejection(s) of claim(s) 1-20 under 35 USC §103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Halimeh et al. (US 2014/0321701 A1).
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1, 14-15, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan et al. (US 9912847 B1) in view of Zou et al. (US 2017/0213371 A1) and Steinberg et al. (US 7702236B2) and Halimeh et al. (US 2014/0321701 A1).
Regarding Claims 1 and 20, Yuan discloses a method via CRM comprising: capturing, using a camera, a first image of a scene that includes a bright object; determining a location of the bright object within the first image [Yuan: Col. 2, ll. 8-37: In at least some embodiments, the computing device can detect a specular reflection, amount of saturation, or region where the detected light exceeds a maximum intensity threshold, for at least a portion of a camera or sensor of the computing device. In response, the computing device can attempt to determine a location or direction of a light source associated with the specular reflection. Once the location or direction is determined, the computing device can attempt to determine a direction or location to which the user should move or adjust the computing device in order to reduce, minimize, or remove the effects of the specular reflection such that a subsequently captured image will be more likely to produce accurate results when provided to an appropriate algorithm, process, or service. The location or direction of the light source can be calculated or estimated using one or more images, which in some embodiments can include images captured at different locations capable of being utilized to provide three-dimensional location information. The three-dimensional location information can be used to determine information such as the position and orientation of the object, as well as the change in position of the specular highlight between image capture positions, which can provide for more accurate light source location determinations. In some embodiments, a camera facing the user can also capture a view on the “front” (user-side) of the device. The view from the front side can be analyzed to attempt to determine the location of shadows, bright spots, or other such aspects on the user to further assist in determining the location of one or more light sources]; and comparing an intensity value of the first object in the first image to a threshold intensity determined based on the determined luminance of the first object [Yuan: Col. 2: the computing device can detect a specular reflection, amount of saturation, or region where the detected light exceeds a maximum intensity threshold, for at least a portion of a camera or sensor of the computing device. In response, the computing device can attempt to determine a location or direction of a light source associated with the specular reflection]; determining, based on the location of the bright object within the first image, an extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image [Yuan: Col. 7, ll. 51-64: Based at least in part upon the determined direction and/or location of the light source, a direction and/or position to which the device should be moved to reduce the saturation in can be determined 612, and information about the direction and/or position can be provided 614 to the user, such as by displaying text or an arrow on a display screen of the computing device. At least one image can then be captured 616 at the new location. The image can be analyzed to determine if an excessive amount of saturation 618 is still present. If an amount of saturation is present in the image that exceeds a saturation threshold, for example, the process of determining the direction of the light source and instructing the user as to a direction to move can continue]; and determining, by comparing the extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image to a predetermined threshold extent of stray light, whether one or more optical imperfections are present on an imaging optic of the camera [Yuan: Col. 7, ll. 51-64].
Yuan may not explicitly disclose wherein determining the location of the bright object within the first image comprises: determining a luminance of a first object in the scene based on a second image that was previously captured (emphasis added), wherein determining that one or more optical imperfections are present on the imaging optic of the camera comprises comparing the extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image to a predetermined threshold extent of stray light, and wherein the one or more optical imperfections comprise cracks, air bubbles, scratches, degradation of lens coatings, condensation, or imperfect transparency.
However, Zou discloses wherein determining the location of the bright object within the first image comprises: determining a luminance of a first object in the scene based on a second image that was previously captured [Zou: Claim 5: compositing the shot current trail image of the moving object with the previous composite trail image of the moving object so as to generate the new trail image of the moving object comprises: determining whether the luminance of a pixel in the shot current trail image of the moving object is greater than the luminance of a pixel, which is at the same position as the position of the pixel of the shot current trail image, in the previous composite trail image of the moving object; and if the luminance of the pixel in the shot current trail image of the moving object is greater than the luminance of the pixel, which is at the same position as the position of the pixel in the shot current trail image, in the previous composite trail image of the moving object, replacing the pixel in the previous composite trail image of the moving object with the pixel, which is at the same position as the position of the pixel in the previous composite trail image, in the shot current trail image of the moving object].
Zou may not explicitly disclose wherein determining that one or more optical imperfections are present on the imaging optic of the camera comprises comparing the extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image to a predetermined threshold extent of stray light, and wherein the one or more optical imperfections comprise cracks, air bubbles, scratches, degradation of lens coatings, condensation, or imperfect transparency.
However, Steinberg discloses wherein determining that one or more optical imperfections are present on the imaging optic of the camera comprises comparing the extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image to a predetermined threshold extent of stray light [Steinberg: Col. 2, ll. 3-10: The device may be arranged to compare two images captured by the sensor when illuminated by the light source, and responsive to the images differing by greater than a threshold amount, to derive the map of defects].
Steinberg may not explicitly disclose cracks, air bubbles, scratches, degradation of lens coatings, condensation, or imperfect transparency.
However, Halimeh discloses wherein the one or more optical imperfections comprise cracks, air bubbles, scratches, degradation of lens coatings, condensation, or imperfect transparency [Halimeh: ¶ [0172]: To prevent unwanted triggering of the wipe/wash function, the images must be evaluated for sharply focused objects on the window pane that do not change even after the pass of the window wiper. Those structures, for example caused by stone impact or cracks, must be recognized and their position and size stored so that they are not mistakenly recognized as rain or contamination].
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the location of luminance measurement based on previous images of Zou to determine the intensity threshold of Yuan in order to provide updated data over time, improving accuracy as well as the defect determination based on a light threshold being reached of Steinberg in order to provide improved situational image processing as well as the structure detection of Halimeh in order to reduce unwanted wiping/wash function.
Regarding Claim 14, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Furthermore, Yuan in view of Zou, Steinberg, and Halimeh discloses wherein the second image is a baseline image captured at a reduced intensity using a secondary camera [Yuan: Col. 8, ll. 26-36: FIG. 7(a) illustrates an example configuration 700 wherein a computing device 702 has a primary camera 704 on a first side of the device and a secondary camera 706 on the second side of the device, although the number and arrangement of cameras can vary by embodiment. In this example, the object 712 is within a field of view of the primary camera 704 and the user is within a field of view of the secondary camera 706].
Regarding Claim 15, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 14, and is/are analyzed as previously discussed with respect to that claim.
Furthermore, Yuan in view of Zou, Steinberg, and Halimeh discloses wherein the secondary camera has a different dynamic range that the camera [Yuan: Col. 8, ll. 18-22: The device might also have a high resolution camera on a side of the phone opposite the display screen in order to capture images of objects, where the display screen can be used as a view finder for the camera].
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan in view of Zou, Steinberg, and Halimeh as applied to claim 1 above, and further in view of Pierce et al. (US 2017/0154425 A1)
Regarding Claim 4, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the threshold intensity is determined using a machine learning algorithm by evaluating a set of labeled training data.
However, Pierce discloses wherein the threshold intensity is determined using a machine learning algorithm by evaluating a set of labeled training data [Pierce: ¶ [0049]: a threshold value for pixel intensity may be used to determine a match. In various embodiments, the threshold values are not provided by human input, but instead are inherently learned by neural network 100 through training].
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the image processing of Yuan in view of Zou, Steinberg, and Halimeh with the AI of Pierce in order to utilize all accompanying capabilities of such.
Claim(s) 5-9 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan in view of Zou, Steinberg, and Halimeh as applied to claim 1 above, and further in view of Alves (US 2017/0195605 A1)
Regarding Claim 5, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the location of the bright object within the image is determined based on a geographical location of the camera.
However, Alves discloses wherein the location of the bright object within the image is determined based on a geographical location of the camera [Alves: ¶ [0010]: The system relies upon environmental, geographic, illumination and electronic sensor response models that provide optimized settings for a given geographic location, camera direction relative to a subject, time of day, time of year and wide range of weather conditions].
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the image processing of Yuan in view of Zou, Steinberg, and Halimeh with the variable system of Alves in order to provide better response to individual conditions.
Regarding Claim 6, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the location of the bright object within the image is determined based on an orientation of the camera.
However, Alves discloses wherein the location of the bright object within the image is determined based on an orientation of the camera [Alves: ¶ [0010]].
Regarding Claim 7, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the location of the bright object within the image is determined based on map data.
However, Alves discloses wherein the location of the bright object within the image is determined based on map data [Alves: ¶ [0010]; wherein map data may be considered any geographic location with coordinates].
Regarding Claim 8, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the location of the bright object within the image is determined based on a time of day.
However, Alves discloses wherein the location of the bright object within the image is determined based on a time of day [Alves: ¶ [0010]].
Regarding Claim 9, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the location of the bright object within the image is determined based on a calendar date.
However, Alves discloses wherein the location of the bright object within the image is determined based on a calendar date [Alves: ¶ [0010]].
Regarding Claim 19, Yuan discloses non-transitory, computer-readable medium having instructions stored thereon, wherein the instructions, when executed by a processor, cause the processor to execute a method comprising: receiving a first image of a scene that includes a bright object, wherein the first image was captured using a camera; determining a location of the bright object within the first image [Yuan: Col. 2, ll. 8-37]; and comparing an intensity value of the first object in the first image to a threshold intensity determined based on the determined luminance of the first object [Yuan: Col. 2]; determining, based on the location of the bright object within the first image, an extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image [Yuan: Col. 7, ll. 51-64; and determining that one or more optical imperfections are present on an imaging optic of the camera [Yuan: Col. 7, ll. 51-64].
Yuan may not explicitly disclose wherein determining the location of the bright object within the first image comprises: determining a luminance of a first object in the scene based on a second image that was previously captured (emphasis added), and wherein the location of the bright object within the first image is further determined based on a geographical location of the camera, an orientation of the camera, map data, a time of day, or a calendar date; wherein determining that one or more optical imperfections are present on the imaging optic of the camera comprises comparing the extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image to a predetermined threshold extent of stray light.
However, Zou discloses wherein determining the location of the bright object within the first image comprises: determining a luminance of a first object in the scene based on a second image that was previously captured [Zou: Claim 5: compositing the shot current trail image of the moving object with the previous composite trail image of the moving object so as to generate the new trail image of the moving object comprises: determining whether the luminance of a pixel in the shot current trail image of the moving object is greater than the luminance of a pixel, which is at the same position as the position of the pixel of the shot current trail image, in the previous composite trail image of the moving object; and if the luminance of the pixel in the shot current trail image of the moving object is greater than the luminance of the pixel, which is at the same position as the position of the pixel in the shot current trail image, in the previous composite trail image of the moving object, replacing the pixel in the previous composite trail image of the moving object with the pixel, which is at the same position as the position of the pixel in the previous composite trail image, in the shot current trail image of the moving object].
Zou may not explicitly disclose wherein the location of the bright object within the first image is further determined based on a geographical location of the camera, an orientation of the camera, map data, a time of day, or a calendar date; and wherein determining that one or more optical imperfections are present on the imaging optic of the camera comprises comparing the extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image to a predetermined threshold extent of stray light.
However, Steinberg discloses wherein determining that one or more optical imperfections are present on the imaging optic of the camera comprises comparing the extent of diffuse veiling glare or lens flare from the bright object that is represented in the first image to a predetermined threshold extent of stray light [Steinberg: Col. 2, ll. 3-10: The device may be arranged to compare two images captured by the sensor when illuminated by the light source, and responsive to the images differing by greater than a threshold amount, to derive the map of defects].
Steinberg may not explicitly disclose wherein the location of the bright object within the first image is further determined based on a geographical location of the camera, an orientation of the camera, map data, a time of day, or a calendar date.
However, Alves discloses wherein the location of the bright object within the first image is further determined based on a geographical location of the camera, an orientation of the camera, map data, a time of day, or a calendar date [Alves: ¶ [0010]].
Claim(s) 10 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan in view of Zou, Steinberg, and Halimeh as applied to claims 1 and 15 above, and further in view of Von Schoyck et al. (US 2018/0068962 A1)
Regarding Claim 10, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the second image is a baseline image captured at a reduced intensity using the camera.
However, Van Schoyck discloses wherein the second image is a baseline image captured at a reduced intensity using the camera [Van Schoyck: ¶ [0062] In some embodiments, the defect detection module 322 may compare an image of a reference element to a baseline image of the reference element. The reference element may be, for example, a known component of the robotic vehicle itself, which may be captured by rotating a gimbal-mounted camera. Alternatively, the reference element may be a known feature or collection of features in the surrounding environment at a predetermined location, such as a home landing pad. The defect detection module 322 may identify regions of the captured image in which features differ from the baseline image by more than a threshold amount, which may be classified as representing defects.
[0063]: In various embodiments, the comparison of features within a captured image of to those of another image (e.g., successively captured image or baseline image) may be performed by comparing pixels based on a luminance intensity or other visual property].
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the image processing of Yuan in view of Zou, Steinberg, and Halimeh with the comparison processes of Van Schoyck in order to improve accuracy.
Regarding Claim 16, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 15, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the secondary camera has a different ISO sensitivity, exposure time, or aperture size than the camera.
However, Van Schoyck discloses wherein the secondary camera has a different ISO sensitivity, exposure time, or aperture size than the camera [Van Schoyck: ¶ [0035]].
Claim(s) 10 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan in view of Zou, Steinberg, and Halimeh as applied to claim 1 above, and further in view of Skinner et al. (US 2015/0186988 A1).
Regarding Claim 10, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the second image was captured by the camera at a substantially similar perspective relative to the scene as the first image.
However, Skinner discloses wherein the second image was captured by the camera at a substantially similar perspective relative to the scene as the first image [Skinner: ¶ [0120]: In embodiments where video data was captured at block 710, one or more frames of the captured image data may be selected for comparison to the baseline data set. Such a selection is based on one or more frames of image data included in the baseline data set. For instance, frames in the captured image data may be automatically selected that provided similar views of the property to the image data included in the baseline data set. Thus, capturing video provides for a more likely opportunity to match the data included in the baseline data set because of the increased number of frames to choose from.
[0121]: To perform the comparison, a relevant portion of the current image data is selected. This selection is based on data included in the baseline data set. The relevant portion includes portions of image data that are relevant for the comparison to baseline data. For instance, the relevant portion may include a subset of a single frame or multiple frames of the captured image data. In embodiments where video data was captured at block 710, the relevant portion may include one or more frames of the captured image data selected for comparison to the baseline data set. Such a selection is based on one or more frames of image data included in the baseline data set. For instance, frames in the captured image data may be automatically selected that provided similar views of the property to the image data included in the baseline data set. Thus, as noted above, capturing video provides for a more likely opportunity to match the data included in the baseline data set because of the increased number of frames to choose from].
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the image processing of Yuan in view of Zou, Steinberg, and Halimeh with the comparison of Skinner in order to improve matching probabilities.
Regarding Claim 12, Yuan in view of Zou, Steinberg, Halimeh and Skinner disclose(s) all the limitations of Claim 10, and is/are analyzed as previously discussed with respect to that claim.
Furthermore, Yuan in view of Zou, Steinberg, Halimeh and Skinner discloses wherein the second image was captured by the camera using a different ISO sensitivity, aperture size, or exposure time than used to capture the first image [Van Schoyck: ¶ [0035]: Each of the cameras 127 may include sub-components other than image capturing sensors, including auto-focusing circuitry, ISO adjustment circuitry, and shutter speed adjustment circuitry, etc.].
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan in view of Zou, Steinberg, Halimeh, and Skinner as applied to claim 10 above, and further in view of Cui et al. (US 10281916 B1).
Regarding Claim 13, Yuan in view of Zou, Steinberg, Halimeh, and Skinner disclose(s) all the limitations of Claim 10, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, Halimeh, and Skinner may not explicitly disclose wherein second image was captured by the camera using a polarization filter to filter out polarizations that are emitted or reflected by the bright object.
However, Cui discloses wherein second image was captured by the camera using a polarization filter to filter out polarizations that are emitted or reflected by the bright object [Cui: Col. 2, l. 59 – Col. 3, l. 4: For example, when glare is removed from a first image including a watery scene (e.g., by using a first polarization filter), certain differences with respect to a second image may be identified. These differences can include texture (e.g., information about the spatial arrangement of color or intensities in an image or a selected region of an image), differences in brightness (e.g., certain colors in the first image may appear brighter as compared to the second image), and/or differences in features (e.g., objects below the water may stand out in the first image and be invisible in the second image). In this manner, the UAV may classify certain pixels and/or the entire image as including a transparent element (e.g., water, ice, glass, mirror, etc.)].
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the image processing of Yuan in view of Zou, Steinberg, Halimeh, and Skinner with the polarizing filter of Cui in order to provide improved digital vision.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan in view of Zou, Steinberg, and Halimeh as applied to claim 1 above, and further in view of Cui et al. (US 10281916 B1).
Regarding Claim 18, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 1, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the first image and the second image were captured from different perspectives relative to the scene, wherein determining the location of the bright object within the first image comprises performing image processing on the first image or the second image such that the perspective relative to the scene is the same for the first image and the second image.
However, Cui discloses wherein the first image and the second image were captured from different perspectives relative to the scene, wherein determining the location of the bright object within the first image comprises performing image processing on the first image or the second image such that the perspective relative to the scene is the same for the first image and the second image [Cui: Col. 14, l. 65 – Col. 15, l. 5: The second image 716 may be captured at or around the same time as the first image 708 and from a similar perspective (e.g., by using the same image capture device or a different image capture device having a similar mounting position and orientation with respect to the scene 710). In this manner, the two images 708, 716 may correspond to roughly the same area of the scene 710], and wherein performing image processing comprises scaling, adjusting the contrast, cropping, or rotating the first image or the second image [Cui: Col. 10, ll. 56-65: For example, such techniques may include edge detection, recognition by parts, appearance-based method (e.g., edge matching, divide-and-conquer, grayscale matching, gradient matching, histograms of receptive field responses, large modelbases, and the like), feature-based method (e.g., interpretation trees, hypothesize and test, pose consistency, pose clustering, invariance, geometric hashing, scale-invariant feature transform (SIFT), and the like].
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the image processing of Yuan in view of Zou, Steinberg, and Halimeh with the polarizing filter of Cui in order to provide improved digital vision.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan in view of Zou, Steinberg, and Halimeh as applied to claim 15 above, and further in view of Powers et al. (US 2017/0195654 A1).
Regarding Claim 17, Yuan in view of Zou, Steinberg, and Halimeh disclose(s) all the limitations of Claim 15, and is/are analyzed as previously discussed with respect to that claim.
Yuan in view of Zou, Steinberg, and Halimeh may not explicitly disclose wherein the secondary camera comprises an optical filter used to reduce light intensity from the scene incident on an image sensor of the secondary camera.
However, Powers discloses wherein the secondary camera comprises an optical filter used to reduce light intensity from the scene incident on an image sensor of the secondary camera [Powers: ¶ [0032]: Accordingly, the apparatus 100 contains the first and second cameras 1, 2 that are utilized in producing 3D images of a scene. Each of the first camera 1 and the second camera 2 is equipped with a housing designed to hold a single- or multi-part lens and an optical filter].
It would have been obvious to one having ordinary skill in the art before the effective filing date to combine the image processing of Yuan in view of Zou, Steinberg, and Halimeh with the optical filtering of Powers in order to provide variably adjustable sensors.
Conclusion
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/JONATHAN R MESSMORE/Primary Examiner, Art Unit 2482
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