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 .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3, 9, 12, 14, 15, 32 and 33 are rejected under 35 U.S.C. 103 as being unpatentable over Dong et al. (US PGPub 2012/0075353) in view of Mandavilli et al. (US PGPub 2019/0342491)
Regarding claim 1, Dong discloses a device (fig. 1, system 10) comprising:
a display module including a display panel (fig. 1, display 12);
a first processor (fig. 1, pixel adjustment 22, which could be a processor as described in [0017]) in signal communication with the display panel (fig. 1, elements 22 and 12 connected at least via signal line 23), the first processor configured to receive an input display signal (fig. 1, image pixel data 11) and provide image data to the display panel (fig. 1, adjusted image pixel data 23); and
a second processor (fig. 1, image statistics generator 16 and adaptive contrast enhancement controller 18, which could be a processor as described in [0017]) configured to receive the input display signal (fig. 1, image pixel data 11) and provide display panel behavior adjustment data to the display panel based on the input display signal ([0020], “Based on these image statistics data 17 and the instructions of the algorithm 20, the adaptive contrast enhancement controller 18 generates backlight control data 19b for adjusting the brightness of the backlight 14 for the display 12, and pixel control data 19p for modifying the original incoming image pixel data 11 to provide adjusted image pixel data 23”), the display panel behavior adjustment data indicating an adjustment to an operational behavior of the display panel based on a characteristic of the input display signal ([0019], “The image statistics generator 16 generates image statistics (e.g., histogram and luma) data 17…for processing by the adaptive contrast enhancement controller 18 in accordance with an algorithm 20, which can be hardwired circuitry or stored as firmware either within or otherwise available to the adaptive contrast enhancement controller 20, e.g., via one or more data buses or a network”),
wherein the first processor, the second processor, or a combination thereof is configured to alter the operational behavior of the display panel based on the display panel behavior adjustment data ([0020], “Based on these image statistics data 17 and the instructions of the algorithm 20, the adaptive contrast enhancement controller 18 generates backlight control data 19b for adjusting the brightness of the backlight 14 for the display 12, and pixel control data 19p for modifying the original incoming image pixel data 11 to provide adjusted image pixel data 23”).
While Dong teaches adjusting the display panel based on brightness, it has been known to perform different adjustments based on different image data characteristics. In a similar field of endeavor of image processing, Mandavilli discloses wherein the characteristic of the input display signal is selected from the group consisting of: a presence of a static icon, a presence of a face, and a presence of artificial image data (fig. 5, step 506, facial detection and recognition);
wherein the adjustment to the operational behavior of the display panel comprises one or more selected from a group consisting of:
lowering a blue saturation based on a detection of a static icon;
adjusting a white point color temperature, a color gamut, a blue content, or a combination thereof based on detecting one or more faces; and
decreasing a blue saturation, a white point color temperature, or a combination thereof based on detecting artificial image data (fig. 5, step 510 perform...white balance based on image data...that includes device owner’s face).
In view of the teachings of Dong and Mandavilli, it would have been obvious to one of ordinary skill in the art to detect a face, as taught by Mandavilli, for the purpose of improving a user’s experience with a device based on improving display characteristics when a user’s face is detected.
Regarding claim 3, the combination of Dong and Mandavilli further discloses wherein the characteristic of the input display signal is selected from the group consisting of: wherein the characteristic of the input display signal is selected from the group consisting of: a presence of a face; and a presence of an artificial image; and wherein the adjustment to the operational behavior of the display panel comprises is selected from the group consisting of: adjusting a white point color temperature, a blue content, or a combination thereof based on detecting one or more faces; and decreasing a blue saturation, a white point color temperature, or a combination therefor based on detecting artificial image data (Mandavilli: [0077]-[0078], “[0077] At block 508, a determination is made as to whether the face of the primary user was recognized. For example, the priority subject selector 146 can compare a face within the first image data within the FOV against one or more stored images of the primary user's face stored in the storage medium 110. If the primary user is recognized, execution proceeds to block 512. If the primary user is detected, the method proceeds to block 510. At block 510, the ROI used for at least one of automatic focus, automatic exposure, or automatic white balance is adjusted based on identification of one or more faces within the field of view of the device that includes the primary user's face. For example, one or more of automatic focus, automatic exposure, or automatic white balance parameters can be adjusted. Then AF, AE and/or AWB is performed using the adjusted parameters.”).
Regarding claim 9, Dong further discloses further comprising:
an ambient light sensor (Dong: [0057], external ambient light sensor);
wherein the first processor is further configured to adjust the operational behavior of the display panel based on a brightness of ambient light detected by the ambient light sensor (Dong: [0057], “The adaptive contrast enhancement controller 18, in accordance with the algorithm 20, takes this "next backlight brightness level" and multiplies it with an "ambient light" adjustment factor (a value ranging from zero to unity obtained from an external ambient light sensor), which is read by the algorithm 20 from elsewhere within the system 10, to determine the "next backlight level", backlight adjustment 19b, to set in the backlight controller 14 associated with the display 12”.
Regarding claim 12, Dong further discloses wherein the display panel comprises an organic light emitting diode (OLED) display, a light emitting diode (LED) or micro-LED display, a quantum dot-based display, a liquid crystal display (LCD), or a combination thereof (Dong: [0002], “displays, such as liquid crystal display (LCD) panels”).
Regarding claim 14, Dong further discloses wherein the first processor and/or the second processor comprises a plurality of physical computer processors (Dong: [0017], “Thus, for example, one or more of the functional blocks (e.g., processors, memories, etc.) may be implemented in a single piece of hardware (e.g., a general purpose signal processor, random access memory, hard disk drive, etc.)”).
Regarding claim 15, Dong further discloses wherein the second processor is the same processor as the first processor (Dong: [0017], “Thus, for example, one or more of the functional blocks (e.g., processors, memories, etc.) may be implemented in a single piece of hardware (e.g., a general purpose signal processor, random access memory, hard disk drive, etc.)”).
Regarding claim 32, the combination of Dong and Mandavilli further discloses wherein the adjustment to the operational behavior of the display panel based on the characteristic of the input display signal comprises one or more selected from a group consisting of:
lowering a blue saturation based on a detection of a static icon;
increasing a display resolution based on video content having a detail level over a threshold;
adjusting a white point color temperature, a color gamut, a blue content, or a combination thereof based on detecting one or more faces; and
decreasing a blue saturation, a white point color temperature, or a combination thereof based on detecting artificial image data (Mandavilli: [0077]-[0078], “[0077] At block 508, a determination is made as to whether the face of the primary user was recognized. For example, the priority subject selector 146 can compare a face within the first image data within the FOV against one or more stored images of the primary user's face stored in the storage medium 110. If the primary user is recognized, execution proceeds to block 512. If the primary user is detected, the method proceeds to block 510. At block 510, the ROI used for at least one of automatic focus, automatic exposure, or automatic white balance is adjusted based on identification of one or more faces within the field of view of the device that includes the primary user's face. For example, one or more of automatic focus, automatic exposure, or automatic white balance parameters can be adjusted. Then AF, AE and/or AWB is performed using the adjusted parameters.”).
Claim 33 is within the scope of claim 32 and is therefore interpreted and rejected based on similar reasoning.
Claims 26, 27, 29 and 34 are rejected under 35 U.S.C. 103 as being unpatentable over Dong in view of Park et al. (US PGPub 2014/0225933) and Mandavilli.
Regarding claim 26, Dong discloses a consumer electronic device (fig. 1, system 10, which could be incorporated into an apparatus as described in [0018]) comprising:
a display module including a display panel (fig. 1, display 12);
a first processor (fig. 1, pixel adjustment 22, which could be a processor as described in [0017]) in signal communication with the display panel (fig. 1, elements 22 and 12 connected at least via signal line 23), the first processor configured to receive an input display signal (fig. 1, image pixel data 11) and provide image data to the display panel (fig. 1, adjusted image pixel data 23); and
a second processor (fig. 1, image statistics generator 16 and adaptive contrast enhancement controller 18, which could be a processor as described in [0017]) configured to receive the input display signal (fig. 1, image pixel data 11) and provide display panel behavior adjustment data to the display panel processor based on the input display signal ([0020], “Based on these image statistics data 17 and the instructions of the algorithm 20, the adaptive contrast enhancement controller 18 generates backlight control data 19b for adjusting the brightness of the backlight 14 for the display 12, and pixel control data 19p for modifying the original incoming image pixel data 11 to provide adjusted image pixel data 23”), the display panel behavior adjustment data indicating an first adjustment to an operational behavior of the display panel based on a characteristic of the input display signal ([0019], “The image statistics generator 16 generates image statistics (e.g., histogram and luma) data 17…for processing by the adaptive contrast enhancement controller 18 in accordance with an algorithm 20, which can be hardwired circuitry or stored as firmware either within or otherwise available to the adaptive contrast enhancement controller 20, e.g., via one or more data buses or a network”);
wherein the first processor, the second processor, or a combination thereof is configured to alter the operational behavior of the display panel based on the display panel behavior adjustment data ([0020], “Based on these image statistics data 17 and the instructions of the algorithm 20, the adaptive contrast enhancement controller 18 generates backlight control data 19b for adjusting the brightness of the backlight 14 for the display 12, and pixel control data 19p for modifying the original incoming image pixel data 11 to provide adjusted image pixel data 23”); and
wherein the consumer electronic device is at least one type selected from the group consisting of: a flat panel display, a curved display, a computer monitor, a medical monitor, a television, a billboard, a light for interior or exterior illumination and/or signaling, a heads-up display, a fully or partially transparent display, a flexible display, a rollable display, a foldable display, a stretchable display, a laser printer, a telephone, a cell phone, tablet, a phablet, a personal digital assistant (PDA), a wearable device, a laptop computer, a digital camera, a camcorder, a viewfinder, a micro-display that is less than 2 inches diagonal, a 3-D display, a virtual reality or augmented reality display, a vehicle, a video walls comprising multiple displays tiled together, a theater or stadium screen, and a sign ([0018], “As is well known in the art, a system such as that disclosed herein is suitable for incorporation into or use with many types of higher level apparatuses having displays, including, but not limited to, computer systems, handheld devices, high definition televisions (e.g., capable of accepting computer signals for use as a computer monitor), or other suitable electronic systems”).
While Dong teaches adjusting the display panel based on brightness, it has been known to perform different adjustments based on different image data characteristics. In a similar field of endeavor of image processing, Park discloses
wherein the adjustment to the operational behavior of the display panel comprises one or more selected from a group consisting of:
a green to blue ratio;
a red to green ratio; and
a blue saturation ([0090]: “The saturation adjuster 230 generates the compensation image data signal SDATA and sends RGB data having increased saturation to the luminance calculator 210, the saturation calculator 220, and the power consumption calculator 240”).
In view of the teachings of Dong and Park, it would have been obvious to one of ordinary skill in the art to perform adjustment based on luminance, as taught by Park, within the system of Dong, for the purpose of reducing power consumption despite increasing saturation to improve the external visibility of the display device (Park: [0008]).
While the combination of Dong and Park discloses adjusting a display panel based on brightness, it has been known to perform different adjustments based on different image data characteristics such as detection of a face causing white point adjustment. In a similar filed of endeavor of display devices, Mandavilli further discloses wherein the first characteristic of the input display signal is selected from the group consisting of: white point, frame rate and resolution ([0064], “And the white balance is selected to minimize the total color temperature error among all three faces, but does not guarantee the best possible color temperature for any individual one of the three faces”).
In view of the teachings of Dong, Park and Mandavilli, it would have been obvious to one of ordinary skill in the art to perform adjustment based on white point, as taught by Mandavilli, within the system of Dong and Park, for the purpose of selecting a known characteristic from a group of input display signal characteristics to improve a user’s experience with a device.
Regarding claim 27, Dong further discloses wherein the second processor is the same processor as the first processor (Dong: [0017], “Thus, for example, one or more of the functional blocks (e.g., processors, memories, etc.) may be implemented in a single piece of hardware (e.g., a general purpose signal processor, random access memory, hard disk drive, etc.)”).
Regarding claim 29, Dong discloses a device (fig. 1, system 10) comprising:
a display module including a display panel (fig. 1, display 12);
a first processor (fig. 1, pixel adjustment 22, which could be a processor as described in [0017]) in signal communication with the display panel (fig. 1, elements 22 and 12 connected at least via signal line 23), the first processor configured to receive an original input display signal (fig. 1, image pixel data 11) and provide image data to the display panel (fig. 1, adjusted image pixel data 23); and
a second processor (fig. 1, image statistics generator 16 and adaptive contrast enhancement controller 18, which could be a processor as described in [0017]), configured to receive the input display signal (fig. 1, image pixel data 11) and provide display panel behavior adjustment data to the display processor based on the input display signal ([0020], “Based on these image statistics data 17 and the instructions of the algorithm 20, the adaptive contrast enhancement controller 18 generates backlight control data 19b for adjusting the brightness of the backlight 14 for the display 12, and pixel control data 19p for modifying the original incoming image pixel data 11 to provide adjusted image pixel data 23”), the display panel behavior adjustment data indicating an adjustment to an operational behavior of the display panel based on a characteristic of the input display signal ([0019], “The image statistics generator 16 generates image statistics (e.g., histogram and luma) data 17…for processing by the adaptive contrast enhancement controller 18 in accordance with an algorithm 20, which can be hardwired circuitry or stored as firmware either within or otherwise available to the adaptive contrast enhancement controller 20, e.g., via one or more data buses or a network”);
wherein the first processor, the second processor, or a combination thereof is configured to alter the operational behavior of the display panel based on the display panel behavior adjustment data ([0020], “Based on these image statistics data 17 and the instructions of the algorithm 20, the adaptive contrast enhancement controller 18 generates backlight control data 19b for adjusting the brightness of the backlight 14 for the display 12, and pixel control data 19p for modifying the original incoming image pixel data 11 to provide adjusted image pixel data 23”).
While Dong teaches adjusting the display panel based on brightness, it has been known to perform different adjustments based on different image data characteristics. In a similar field of endeavor of image processing, Park discloses
wherein the adjustment to the operational behavior of the display panel comprises one or more selected from a group consisting of
a green to blue ratio;
a red to green ratio; and
a blue saturation ([0090]: “The saturation adjuster 230 generates the compensation image data signal SDATA and sends RGB data having increased saturation to the luminance calculator 210, the saturation calculator 220, and the power consumption calculator 240”).
In view of the teachings of Dong and Park, it would have been obvious to one of ordinary skill in the art to perform adjustment based on luminance, as taught by Park, within the system of Dong, for the purpose of reducing power consumption despite increasing saturation to improve the external visibility of the display device (Park: [0008]).
While the combination of Dong and Park discloses adjusting a display panel based on brightness, it has been known to perform different adjustments based on different image data characteristics such as detection of a face causing white point adjustment. In a similar filed of endeavor of display devices, Mandavilli further discloses wherein the first characteristic of the input display signal is selected from the group consisting of: white point, frame rate and resolution ([0064], “And the white balance is selected to minimize the total color temperature error among all three faces, but does not guarantee the best possible color temperature for any individual one of the three faces”).
In view of the teachings of Dong, Park and Mandavilli, it would have been obvious to one of ordinary skill in the art to perform adjustment based on white point, as taught by Mandavilli, within the system of Dong and Park, for the purpose of selecting a known characteristic from a group of input display signal characteristics to improve a user’s experience with a device.
Regarding claim 34, while the combination of Dong and Mandavilli discloses adjusting the display panel based on brightness, it has been known to perform different adjustments based on different image data characteristics. In a similar field of endeavor of image processing, Park discloses wherein the adjustment to the operational behavior of the display panel further comprises changing one or more selected from a group consisting of: a green to blue ratio; a red to green ration; and a blue saturation (Park: [0010], “to calculate a compensation ratio based on a rate of change of luminance, a rate of increase of saturation”).
In view of the teachings of Dong, Mandavilli and Park, it would have been obvious to one of ordinary skill in the art to perform adjustment based on luminance, as taught by Park, within the system of Dong and Mandavilli, for the purpose of reducing power consumption despite increasing saturation to improve the external visibility of the display device (Park: [0008]).
Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over Dong and Mandavilli in view of Chou et al. (US PGPub 2019/0075301).
Regarding claim 6, while Dong and Mandavilli teaches multiple processors within a system, it has been known to use artificial intelligence within a processor. In a similar field of endeavor of display devices, Chou discloses wherein the second processor is an artificial intelligence processor ([0082], “To facilitate improving video encoding and/or video decoding, the video encoding pipeline 32 may leverage machine learning techniques implemented by the machine learning block 34. In some embodiments, the machine learning block 34 may be physically implemented in the electronic device 10” where [0095] discusses the use of a processor).
In view of the teachings of Dong, Mandavilli and Chou, it would have been obvious to one of ordinary skill in the art to use the machine learning processor of Chou in the system of Dong and Mandavilli, for the purpose of improving video encoding and/or video decoding, for example, by improving encoding efficiency, decoding efficiency, and/or perceived video quality when decoded image data is used to display an image (e.g., image frame) on an electronic display (Chou: [0008]).
Regarding claim 7, the combination of Dong, Mandavilli and Chou further discloses wherein the artificial intelligence processor is configured to implement a machine learning system that applies a machine learning algorithm to the input display signal to generate the image adjustment data (Chou: [0083], “The machine learning block 34 may implement machine learning parameters 64 to contextually analyze source image data 36, for example, compared with previously processed (e.g., analyzed or encoded) image data to determine expected characteristics of a corresponding image. Based at least in part on the characteristics, the video encoding pipeline 32 may adaptively adjust the encoding parameters in a content dependent manner, which at least in some instances may improve encoding efficiency, decoding efficiency, and/or resulting video quality of decoded image data”).
Regarding claim 8, the combination of Dong, Mandavilli and Chou further discloses wherein the machine learning system comprises a neural network, a convolution neural network, a recurrent neural network, a radial basis function neural network, a multilayer perceptron, a deep belief network, or a combination thereof (Chou: [0083], “the machine learning block 34 may implement convolutional neural network (CNN) techniques”).
Claims 10, 11 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Dong and Mandavilli in view of Lee et al. (US PGPub 2022/0217325).
Regarding claim 10, while Dong and Mandavilli teaches adjusting a display performance based on image data, it has been known to perform the adjustment based on a user’s gaze. In a similar field of endeavor of display devices, Lee discloses further comprising:
a gaze detection sensor configured to identify a direction of gaze of a viewer of the display ([0064], “For example, when the electronic device 201 captures the user's pupil by using the second camera module (e.g., the third camera 235 and the fourth camera 237), the electronic device 201 may easily detect the user's gaze by using the first LED 241 and the second LED 243 as the auxiliary lighting. For example, the first LED 241 and the second LED 243 may include an infrared (IR) LED having an infrared wavelength. Even in a dark environment or an environment where a plurality of lighting elements emit light that are mixed and incident or reflected, the electronic device 201 may easily detect a subject with a camera module, by using the first LED 241 and the second LED 243 as the auxiliary lighting”);
wherein the first processor is further configured to adjust the operational behavior of the display panel based on the direction of gaze detected by the gaze detection sensor ([0118], “In operation 507, the electronic device may control at least one of a setting of a display and an output setting of content depending on the determined eye fatigue level. According to an embodiment, an item related to the setting of the display may include at least one of scan rate and brightness. An item related to the output setting of content may include at least one of the number, sizes, locations, colors, or stereoscopic effect levels of objects output to the display. For example, the electronic device may change at least one of the scan rate or brightness of the display depending on the eye fatigue level. As another example, the electronic device may change at least one of the number, sizes, locations, colors, or stereoscopic effect levels of objects output to the display depending on the eye fatigue level”).
In view of the teachings of Dong, Mandavilli and Lee, it would have been obvious to one of ordinary skill in the art to include the gaze detection of Lee, in the system of Dong and Mandavilli, for the purpose of improving user experience by reducing symptoms of eye fatigue (Lee: [0007]-[0008]).
Regarding claim 11, the combination of Dong, Mandavilli and Lee further discloses wherein the gaze detection sensor comprises one or more components selected from the group consisting of: an infrared (IR) sensor, a still camera, and a video camera (Lee: [0064], “For example, when the electronic device 201 captures the user's pupil by using the second camera module (e.g., the third camera 235 and the fourth camera 237), the electronic device 201 may easily detect the user's gaze by using the first LED 241 and the second LED 243 as the auxiliary lighting. For example, the first LED 241 and the second LED 243 may include an infrared (IR) LED having an infrared wavelength. Even in a dark environment or an environment where a plurality of lighting elements emit light that are mixed and incident or reflected, the electronic device 201 may easily detect a subject with a camera module, by using the first LED 241 and the second LED 243 as the auxiliary lighting”).
Regarding claim 13, Dong and Mandavilli further discloses wherein the display panel behavior adjustment data is based on the overall input display signal over the entire active area of the display panel (Dong: [0025], “The image statistics generator 16 determines brightness distribution of pixels in a frame of the incoming image pixel data”). While Dong and Mandavilli teaches an LCD device, other types of display devices are known including OLED devices. In a similar field of endeavor of display devices, Lee discloses wherein the display panel comprises an OLED display ([0054], “the display may include a liquid crystal display (LCD), a digital mirror device (DMD), a liquid crystal on silicon (LCoS) device, and an organic light emitting diode (OLED), or a micro light emitting diode (micro LED)”.
In view of the teachings of Dong, Mandavilli and Lee, it would have been obvious to one of ordinary skill in the art to use the OLED display of Lee in the system of Dong and Mandavilli, for the purpose of providing known alternative types of display devices to achieve expected and intended results.
Response to Arguments
Applicant’s arguments with respect to claims 1, 26, and 29 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EMILY J FRANK whose telephone number is (571)270-7255. The examiner can normally be reached Monday-Thursday 8AM-6PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benjamin C Lee can be reached at (571)272-2963. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BENJAMIN C LEE/Supervisory Patent Examiner, Art Unit 2629