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 .
1. Claims 1-20 have been examined.
Information Disclosure Statement
2. The information disclosure statement (IDS) submitted on 03/19/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Interpretation
3. For claims 5 and 15, the “or” limitation has been given the broadest, reasonable interpretation of only requiring a single element from the given options in order to satisfy the requirements of the limitation.
4. 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.
Claim Rejections - 35 USC § 103
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.
5. Claims 1-3 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Yuan et al. (U.S. Patent Application Publication 2024/0232359; hereafter “Yuan”), and further in view of Tang et al. (U.S. Patent Application Publication 2023/0328386; hereafter “Tang”).
For claim 1, Yuan teaches an intelligent method for logging in an operating system, comprising:
retrieving brightness information of the image (note paragraphs [0256] and [0300], intensity value of ambient light is obtained);
operating a scene-prediction model to predict a scene according to the brightness information (note paragraphs [0260]-[0262], environment, i.e. scene, is predicted based on the intensity of the light value) and obtain an exposure setting corresponding to the scene (note paragraphs [0136], [0247]-[0248], AE, automatic exposure, is obtained that corresponds to indoor or outdoor scene; paragraph [0301]-[0313], exposure duration is obtained that corresponds to current environment);
activating an IR camera to generate an infrared image according to the exposure setting (note paragraphs [0095]-[0096], [0142] and [0312], TOF camera, i.e. IR camera, is activated according to AE); and
using a biometric image extracted from the infrared image to log in the operating system after identification is processed (note paragraphs [0080], [0116]-[0117] and [0123], face, i.e. biometric, image is extracted from TOF image and used for authentication and unlock a device and log in to an operating system).
Yuan differs from the claimed invention in that they fail to teach:
capturing a color image, and retrieving brightness information of the color image;
Tang teaches:
capturing a color image (note paragraph [0152] and [0204], RGB images of the environment are captured), and retrieving brightness information of the color image (note paragraph [0177], amount of brightness is calculated from RGB images);
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the biometric authentication using IR images of Yuan and the determination of brightness of an environment using RGB images of Tang. It would have been obvious because a simple substitution of one known element (determining brightness using captured RGB images of Tang) for another (determining brightness using an ambient light sensor of Yuan) would yield the predictable results of determining brightness of the environment using RGB images (Tang) where the brightness is used to determine the scene and automatic exposure for the IR camera to capture biometric data (Yuan).
For claim 10, the combination of Yuan and Tang teaches a system for performing an intelligent method for logging in an operating system, comprising:
a computer system, wherein the computer system includes a camera system, and the camera system includes a color camera (note paragraphs [0059]-[0060] of Tang, RGB-IR camera), an IR camera, and an IR light source (note paragraphs [0067]-[0070] of Yuan, electronic device with TOF camera and TOF light source);
wherein the computer system operates the operating system (note paragraph [0080] of Yuan, operating system), and the intelligent method that is performed includes:
using the color camera to capture a color image (note paragraph [0152] and [0204] of Tang, RGB images of the environment are captured), and retrieving brightness information of the color image (note paragraph [0177] of Tang, amount of brightness is calculated from RGB images);
operating a scene-prediction model to predict a scene according to the brightness information (note paragraphs [0260]-[0262] of Yuan, environment, i.e. scene, is predicted based on the intensity of the light value) and an exposure setting corresponding to the scene (note paragraphs [0136], [0247]-[0248] of Yuan, AE, automatic exposure, is obtained that corresponds to indoor or outdoor scene; paragraph [0301]-[0313] of Yuan, exposure duration is obtained that corresponds to current environment);
activating the IR camera to generate an infrared image according to the exposure setting (note paragraphs [0095]-[0096], [0142] and [0312] of Yuan, TOF camera, i.e. IR camera, is activated according to AE); and
using a biometric image extracted from the infrared image to log in the operating system after identification is processed (note paragraphs [0080], [0116]-[0117] and [0123] of Yuan, face, i.e. biometric, image is extracted from TOF image and used for authentication and unlock a device and log in to an operating system).
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the biometric authentication using IR images of Yuan and the determination of brightness of an environment using RGB images of Tang. It would have been obvious because a simple substitution of one known element (determining brightness using captured RGB images of Tang) for another (determining brightness using an ambient light sensor of Yuan) would yield the predictable results of determining brightness of the environment using RGB images (Tang) where the brightness is used to determine the scene and automatic exposure for the IR camera to capture biometric data (Yuan).
For claim 2, the combination of Yuan and Tang teaches claim 1, wherein, after the exposure setting corresponding to the scene is obtained, the IR camera is activated to capture continuous frames of a user (note paragraphs [0270]-[0272] of Yuan, TOF camera is powered on and captures groups of frames with the TOF light source turned on, i.e. bright frame, and then turned off, i.e. dark frame), and the exposure setting takes effect on a first bright frame of the continuous frames, so as to obtain the biometric image having an appropriate exposure (note paragraphs [0312]-[0313] of Yuan, TOF sensor controller receives exposure duration to obtain TOF data with appropriate exposure).
For claim 3, the combination of Yuan and Tang teaches claim 2, wherein, when the IR camera is activated, an IR light source is driven to illuminate the user, so as to obtain the continuous frames having a series of bright and dark frames (note paragraphs [0270]-[0272] of Yuan, TOF camera is powered on and captures groups of frames with the TOF light source turned on, i.e. bright frame, and then turned off, i.e. dark frame).
6. Claims 4-5 and 11-15 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Yuan and Tang as applied to claims 1 and 10 above, and further in view of Sinha et al. (U.S. Patent Application Publication 2022/0414198; hereafter “Sinha”).
For claim 4, the combination of Yuan and Tang teaches claim 1, wherein the intelligent method is operated in a system (note paragraphs [0067]-[0070] of Yuan, electronic device with TOF camera and TOF light source); wherein, a color camera is activated to capture the color image (note paragraph [0152] and [0204] of Tang, RGB images of the environment are captured) for completing the process of predicting the scene (note paragraph [0177] of Tang, amount of brightness is calculated from RGB images; paragraphs [0260]-[0262] of Yuan, environment, i.e. scene, is predicted based on the intensity of the light value) and obtaining the exposure setting before the IR camera is activated (note paragraphs [0136], [0247]-[0248] of Yuan, AE, automatic exposure, is obtained that corresponds to indoor or outdoor scene; paragraph [0301]-[0313] of Yuan, exposure duration is obtained that corresponds to current environment).
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the biometric authentication using IR images of Yuan and the determination of brightness of an environment using RGB images of Tang. It would have been obvious because a simple substitution of one known element (determining brightness using captured RGB images of Tang) for another (determining brightness using an ambient light sensor of Yuan) would yield the predictable results of determining brightness of the environment using RGB images (Tang) where the brightness is used to determine the scene and automatic exposure for the IR camera to capture biometric data (Yuan).
The combination of Yuan and Tang differs from the claimed invention in that they fail to teach:
in a booting procedure after the system is started up, a color camera is activated to capture the color image for completing the process
Sinha teaches:
in a booting procedure after the system is started up, a color camera is activated to capture the color image for completing the process (note paragraph [0044], camera is activated to perform facial authentication as part of a boot procedure),
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the combination of Yuan and Tang and the facial authentication during a boot procedure of Sinha. One of ordinary skill would have been motivated to combine Yuan, Tang and Sinha because it would increase security by only allowing authorized users to boot a device.
For claim 5, the combination of Yuan, Tang and Sinha teaches claim 4, wherein the system uses a machine vision processor to determine the brightness information according to the color image (note paragraph [0177] of Tang, amount of brightness is calculated from RGB images by average intensity module), and uses the scene-prediction model to identify whether the scene is an indoor scene, a front-light scene, a back-light scene, an outdoor scene, or a low-light scene (paragraphs [0260]-[0262] of Yuan, environment, i.e. scene, is predicted includes indoor and outdoor scenes).
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the biometric authentication using IR images of Yuan and the determination of brightness of an environment using RGB images of Tang. It would have been obvious because a simple substitution of one known element (determining brightness using captured RGB images of Tang) for another (determining brightness using an ambient light sensor of Yuan) would yield the predictable results of determining brightness of the environment using RGB images (Tang) where the brightness is used to determine the scene and automatic exposure for the IR camera to capture biometric data (Yuan).
For claim 11, the combination of Yuan, Tang and Sinha teaches claim 10, wherein, in a booting procedure after the system is started up (note paragraph [0044] of Sinha, camera is activated to perform facial authentication as part of a boot procedure), the color camera is activated to capture the color image (note paragraph [0152] and [0204] of Tang, RGB images of the environment are captured) for completing the process of predicting the scene (note paragraph [0177] of Tang, amount of brightness is calculated from RGB images; paragraphs [0260]-[0262] of Yuan, environment, i.e. scene, is predicted based on the intensity of the light value) and obtaining the exposure setting before the IR camera is activated (note paragraphs [0136], [0247]-[0248] of Yuan, AE, automatic exposure, is obtained that corresponds to indoor or outdoor scene; paragraph [0301]-[0313] of Yuan, exposure duration is obtained that corresponds to current environment).
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the biometric authentication using IR images of Yuan and the determination of brightness of an environment using RGB images of Tang. It would have been obvious because a simple substitution of one known element (determining brightness using captured RGB images of Tang) for another (determining brightness using an ambient light sensor of Yuan) would yield the predictable results of determining brightness of the environment using RGB images (Tang) where the brightness is used to determine the scene and automatic exposure for the IR camera to capture biometric data (Yuan).
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the combination of Yuan and Tang and the facial authentication during a boot procedure of Sinha. One of ordinary skill would have been motivated to combine Yuan, Tang and Sinha because it would increase security by only allowing authorized users to boot a device.
For claim 12, the combination of Yuan, Tang and Sinha teaches claim 11, wherein, after the exposure setting corresponding to the scene is obtained, the IR camera is activated to capture continuous frames of a user (note paragraphs [0270]-[0272] of Yuan, TOF camera is powered on and captures groups of frames with the TOF light source turned on, i.e. bright frame, and then turned off, i.e. dark frame), and the exposure setting takes effect on a first bright frame of the continuous frames, so as to obtain the biometric image having an appropriate exposure (note paragraphs [0312]-[0313] of Yuan, TOF sensor controller receives exposure duration to obtain TOF data with appropriate exposure).
For claim 13, the combination of Yuan, Tang and Sinha teaches claim 12, wherein, when the IR camera is activated, an IR light source is driven to illuminate the user, so as to obtain the continuous frames having a series of bright and dark frames (note paragraphs [0270]-[0272] of Yuan, TOF camera is powered on and captures groups of frames with the TOF light source turned on, i.e. bright frame, and then turned off, i.e. dark frame).
For claim 14, the combination of Yuan, Tang and Sinha teaches claim 13, wherein the system controls a switch of the IR light source to be turned on at a first time, so as to obtain the first bright frame (note paragraphs [0270]-[0272] of Yuan, TOF camera is powered on and captures groups of frames with the TOF light source turned on, i.e. bright frame, and then turned off, i.e. dark frame).
For claim 15, the combination of Yuan, Tang and Sinha teaches claim 11, wherein the system uses a machine vision processor to determine the brightness information according to the color image (note paragraph [0177] of Tang, amount of brightness is calculated from RGB images by average intensity module), and uses the scene-prediction model to identify whether the scene is an indoor scene, a front-light scene, a back-light scene, an outdoor scene, or a low-light scene (paragraphs [0260]-[0262] of Yuan, environment, i.e. scene, is predicted includes indoor and outdoor scenes).
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the biometric authentication using IR images of Yuan and the determination of brightness of an environment using RGB images of Tang. It would have been obvious because a simple substitution of one known element (determining brightness using captured RGB images of Tang) for another (determining brightness using an ambient light sensor of Yuan) would yield the predictable results of determining brightness of the environment using RGB images (Tang) where the brightness is used to determine the scene and automatic exposure for the IR camera to capture biometric data (Yuan).
Allowable Subject Matter
7. Claims 6-9 and 16-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
For claims 6 and 16, the prior art of record, alone or in combination, fails to teach the following limitations in conjunction with the rest of the claimed limitations:
wherein the scene is referred to for calculating a corresponding weight value that is used to map a color exposure setting to an IR exposure setting, so that the exposure setting is obtained, and the IR camera captures the infrared image according to the IR exposure setting.
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hu (U.S. Patent Application Publication 2024/0163566) discloses a deep learning algorithm to predict scene type (note paragraph [0054]) and determining exposure compensation based on the scene type (note paragraph [0049]).
Khemka et al. (U.S. Patent Application Publication 2025/0142207) discloses determining exposure setting from RGB images to accommodate scene lighting (note paragraph [0046]).
Feng et al. (U.S. Patent Application Publication 2017/0091550) discloses first capturing a RGB image at a first exposure time and then capturing an IR image at a second exposure time for biometric authentication (note paragraphs [0059]-[0062]).
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID J PEARSON whose telephone number is (571)272-0711. The examiner can normally be reached 8:30 - 6:00 pm; Monday through Friday.
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, Catherine Thiaw can be reached at (571)270-1138. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
DAVID J. PEARSON
Primary Examiner
Art Unit 2407
/David J Pearson/Primary Examiner, Art Unit 2407
Prosecution Insights