DETAILED ACTION
This Action is in response to Applicant’s response filed on 04/22/2026. Claims 1-20 are still pending in the present application. This Action is made FINAL.
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Talvala (US 2014/0016004 A1).
Regarding claims 1, 8 and 15, Talvala discloses an electronic device, comprising:
a processor and a memory, wherein the memory stores computer execution instructions; and the computer execution instructions, when executed by the processor, cause the processor to: (paragraphs 17-18)
obtain first image data; (abstract, paragraphs 18, 27 and 29: Talvala teaches obtaining first image data by acquiring Initial Sensor Data from either the sensor or from a Raw Input, initiated by an acquire image instruction. Talvala also teaches acquiring a RAW image and reprocessing a stored RAW file from memory.)
determine or generate a target data stream according to a data stream format; and (paragraphs 21 and 30: Talvala teaches generating a target data stream by outputting image-related data and metadata into a structured bundle. Metadata is output to an Output Frame Metadata Queue and, upon a getFrame() request, the RAW image and metadata are moved into a Frame 630 that consolidates the image with associated metadata fields. Additionally , Talvala teaches combining multiple image outputs such as YUV, compressed, video with raw output using a multiplexer and outputting the combined stream to the application.)
wherein the target data stream comprises the first image data and characteristic data of the first image data (paragraph 30: Talvala teaches that Frame 630 includes both the image data and metadata data. The RAW image 592 and metadata 612 are moved to Frame 630, and Frame 630 consolidates the image with associated Capture Request 632, Final Settings 634, Basic Metadata 636, Statistical Output 638, and ByteBuffer 640, where the ByteBuffer holds the image.) the characteristic data of the first image data comprises at least one of the following data items: basic image information (paragraph 19: Talvala teaches that the Statistics Generator retrieves statistics such as date, resolution, flash, and other information relating to the image being acquired, and calculates a histogram), imaging information or semantic information of the first image data (paragraphs 22-23: Talvala teaches camera characteristics including position information, optics information such as focal length and aperture range, sensor information such as maximum resolution, sensor type, and dimensions, and pipeline information including processing categories.) the first image data and the characteristic data are arranged sequentially in a specific order in the target data stream (paragraph 30: Talvala teaches a structured arrangement in Frame 630: when getFrame() is requested, the RAW Image 592 and metadata 612 are moved into Frame 630, and Frame 630 consolidates the image with associated data fields including Capture Request 632, Final Settings 634, Basic Metadata 636, Statistical Output 638, and ByteBuffer 640. This discloses the image and its characteristic data being arranged together in a defined frame structure or order. Talvala also teaches ordered pipeline handling since each pipeline is allocated a slot number, frame size, and frame format, and the Capture Request forms output pipelines containing request information for each pipeline, see paragraphs 24-25. Talvala further teaches an ordered list of requests in the Input Request Queue, and the resulting image and metadata outputs are placed into the image buffer pipeline and metadata queue before being consolidated into Frame 630, see paragraphs 26-27 and 30.)
perform image processing on the first image data according to the target data stream. (paragraphs 20-21 and 30: Talvala teaches performing image processing by preprocessing the raw input using a preprocessor under a preprocessing instruction, for example noise reduction, demosaic, color correction, producing preprocessed data and converted output (YUV, compressed, video) and further processing for viewable formats (JPEG, YPUV) for display or use by the application.)
Regarding claim 2, Talvala discloses the claimed invention wherein the step S3 comprises: parsing the target data stream, and performing image processing on the first image data to obtain second image data and characteristic data of the second image data. (paragraphs 19 and 30: Talvala teaches generating and outputting characteristic data such as statistics (date, resolution, flash) and histogram outputs, and storing metadata and statistical output with the image in frame 630)
Regarding claim 3, Talvala discloses the claimed invention wherein the step S1 comprises at least one of: obtaining the first image data according to an imaging control instruction and/or an image obtaining instruction; (paragraphs 19 and 30: Talvala teaches that the API receives image capture instructions and uses methods such as stream(), capture(), and reprocess() to control acquisition. It also teaches obtaining image data from memory via Raw Input and reprocessing a stored RAW file.) obtaining characteristic data of the first image data. (paragraphs 19 and 30: Talvala teaches obtaining characteristic data by retrieving statistics (date, resolution, flash) and computing a histogram, and also outputting metadata associated with the image and consolidating in in Frame 630 (Basic Metadata, Final Settings, Statistical Output)).
Regarding claim 4, Talvala discloses the claimed invention wherein after the obtaining the characteristic data of the first image data, the method comprises at least one of assigning the basic image information of the first image data to the target data stream; assigning the imaging information of the first image data to the target data stream; assigning the semantic information of the first image data to the target data stream. (see paragraphs 19, 22, 23, 25 and 30: Talvala discloses characteristic data including basic image information and imaging information such as date, resolution, flash, histogram, camera characteristics, final settings, basic metadata, and statistical output, and assigning that data into Frame 630)
Regarding claim 5, Talvala discloses the claimed invention wherein the obtaining the characteristic data of the first image data comprises at least one of: obtaining the basic image information of the first image data through an imaging module of a photography system; obtaining the imaging information of the first image data through at least one of the imaging module and an auxiliary imaging module of the photography system. (paragraphs 15, 19, 22, 23 25 and 30: Talvala discloses obtaining basic information from the camera system and imaging information from camera characteristics and capture request controls such as sensor, lens, 3A control, processing and statistics control.)
Regarding claims 6 and 18, Talvala discloses the claimed invention wherein the step S2 determining or generating the target data stream by arranging respective pieces the data items in the characteristic data in a third specific order. (paragraphs 24, 25, 27 and 30: Talvala discloses generating the target stream by arranging data characteristic information in a defined structure, including pipelines with slot format and Frame 630 with Capture request, final settings, basic metadata, statistical output and bytebuffer.)
Regarding claim 7, Talvala discloses the claimed invention wherein further comprising at least one of: each of the data items comprises at least one type of characteristic information; respective pieces of characteristic information in each of the data items are arranged in a second specific order. (paragraph 30: Talvala discloses that each field in Frame 630 includes characteristic information, and the Frame 630 fields are arranged in a defined frame structure)
Regarding claim 9, Talvala discloses the claimed invention wherein the step S10 comprises at least one of: if the preset rule instructs to add basic image information to a data stream, obtaining basic image information of the first image data through an imaging module of a photography system; if the preset rule instructs to add imaging information to a data stream, obtaining imaging information of the first image data through the imaging module and/or an auxiliary imaging module of the photography system; if the preset rule instructs to add at least one type of semantic information to a data stream, obtaining at least one type of semantic information of the first image data. (paragraphs 19, 22, 23, 25 and 30: Talvala discloses teaches that statistics control causes obtaining basic and imaging information, including statistics, camera characteristics, sensor, lens, 3A settings, final settings, basic metadata, and statistical output)
Regarding claim 10, Talvala discloses the claimed invention wherein if the preset rule instructs to add at least one type of semantic information to a data stream, obtaining at least one type of semantic information of the first image data comprises at least one of: if the preset rule instructs to add basic semantic information to a data stream, obtaining basic semantic information of the first image data; if the preset rule instructs to add optional semantic information to a data stream, obtaining at least one type of optional semantic information of the first image data. (paragraphs 23 and 25: Talvala discloses basic semantic information by disclosing selectable pipeline information such as portrait, sports, flash, video and landscape controls in the capture request.)
Regarding claim 11, Talvala discloses the claimed invention wherein the step S10 comprises: in response to a call to a first interface, obtaining the preset rule from an entry parameter of the first interface, and obtaining the first image data according to the preset rule. (paragraphs 14, 22, 24-25: Talvala teaches that the camera API is initiated by commands such as getCameraInfo() and open(ID), and that open(ID) enables creation of pipelines and createCaptureRequest(), where the capture request includes criteria that control how image data is acquired.)
Regarding claim 12, Talvala discloses the claimed invention wherein the step S20 comprises: in response to a data request from an algorithm module to which a data stream flows, obtaining data required by the algorithm module; (paragraph 30: Talvala teaches that metadata is stored in an Output Frame Metadata Queue and, when requested by getFrame(), the RAW image and metadata are delivered into Frame 630.)and after obtaining the data required by the algorithm module, assigning the obtained data to the data stream to obtain the target data stream. (paragraph 30: Talvala teaches assigning the RAW image and its metadata into Frame 630, which consolidates the image with associated field (Capture Request, Final Settings, Basic Metadata, Statistical Output, ByteBuffer)).
Regarding claim 13, Talvala discloses the claimed invention wherein in response to the data request from the algorithm module to which the data stream flows, obtaining the data required by the algorithm module comprises: in response to a call to a second interface from any algorithm module, determining or obtaining the data required by the algorithm module according to an input parameter of the second interface, and transmitting the obtained data to the algorithm module. (paragraphs 24, 26 and 30: Talvala teaches a second request via getFrame() and API methods, where requested metadata data are determined and consolidated into Frame 630 for the requesting module)
Regarding claim 14, Talvala discloses the claimed invention wherein the step S30 comprises: parsing the target data stream, (paragraph 30: Talvala teaches that, upon a getFrame() request, image and metadata are moved into Frame 630 with defined subfields, enabling access of the contents.) and performing image processing on the first image data to obtain second image data and/or characteristic data of the second image data. (paragraphs 19-21 and 30: Talvala teaches second image data via preprocessing and conversion outputs and characteristics data via statistics and metadata in Frame 630.)
Regarding claim 16, Talvala discloses the claimed invention wherein the computer execution instructions, when executed by the processor, cause the processor to: parse the target data stream, (paragraph 30: Talvala teaches that image and metadata are packaged in Frame 630 when requested by getFrame(), enabling structures access to the contents.) and perform image processing on the first image data to obtain second image data and characteristic data of the second image data. (paragraphs 19-21 and 30: Talvala teaches producing processed image outputs and producing characteristic data.)
Regarding claim 17, Talvala discloses the claimed invention wherein the computer execution instructions, when executed by the processor, cause the processor to perform at least one of: obtaining the first image data according to an imaging control instruction and/or an image obtaining instruction; (paragraphs 5, 18, 26 and 29: Talvala teaches capture instructions via API and acquisition control via stream(), capture(), reprocess(), including obtaining image data from memory.) obtaining characteristic data of the first image data. (paragraphs 19 and 30: Talvala teaches generating characteristic data such as statistics and outputting metadata consolidated in frame 630.)
Regarding claim 19, Talvala discloses the claimed invention wherein a processor and a memory, wherein the memory stores computer execution instructions; and when the computer execution instructions are executed by the processor, the image processing method according to claim 8 is implemented. (paragraphs 17-18)
Regarding claim 20, Talvala discloses the claimed invention wherein a non-transitory computer-readable storage medium, wherein computer execution instructions are stored in the computer-readable storage medium, and when the computer execution instructions are executed by a processor, the image processing method according to claim 1 is implemented. (paragraphs 17-18)
Conclusion
THIS ACTION IS MADE FINAL. 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 BOBBAK SAFAIPOUR whose telephone number is (571)270-1092. The examiner can normally be reached Monday - Friday, 8:00am - 5:00pm.
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/BOBBAK SAFAIPOUR/Primary Examiner, Art Unit 2665
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