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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 02/27/2026 has been entered.
Response to Arguments
Applicant's arguments filed on 02/27/2026 have been fully considered but they are not persuasive for the following reasons.
With the arguments that Lee in view of Kompalli do not teach or disclose the newly amended limitations from the independent claims 1, 13 and 15 as filed on 02/27/2026. The examiner respectfully disagrees because Lee teaches the followings.
With respect to the amended limitations to claim 1, Lee teaches “determining at least a portion of the other handwritten content that relates to the identified key (Lee, Figure 7, pp [107]-[109]: “Call Jill J tonight”: “call” is the identified key, “Jill J tonight” is the other handwritten content relating to the identified key “call”), the at least a portion of the other handwritten content that relates to the identified key defining relevant handwritten content (Lee, Figure 7, pp [107]-[109]: “Call Jill J tonight”: “call” is the identified key, “Jill J tonight” is the other handwritten content relating to the identified key “call”), wherein determining the portion of the other handwritten content that relates to the identified key (Lee, Figure 7, pp [107]-[109]: “Call Jill J tonight”: “call” is the identified key, “Jill J tonight” is the other handwritten content relating to the identified key “call”) comprises identifying handwritten content positioned within a spatial threshold relative to the identified key, wherein the spatial threshold is determined at least in part based on a relative dimension of the key” (Lee, Figure 7, pp [107]-[109]: the content “Jill J tonight” is in close or in a spatial neighboring location to the identified key “call”). Therefore, Lee teaches and discloses the argued limitations, i.e., “determining at least a portion of the other handwritten content that relates to the identified key, the at least a portion of the other handwritten content that relates to the identified key defining relevant handwritten content, wherein determining the portion of the other handwritten content that relates to the identified key comprises identifying handwritten content positioned within a spatial threshold relative to the identified key, wherein the spatial threshold is determined at least in part based on a relative dimension of the key”.
With respect to the amended limitations to claim 13, Lee teaches “identifying the key in the digital representation of the handwritten text from among a plurality of predefined candidate keys (Lee, Figure 7, pp [107]-[109]: “call” is identified as an candidate action key), wherein identifying the key comprises determining that handwritten content is located within a predefined key region mapped to the predetermined action” (Lee, Figure 7, pp [107]-[109]: the content “Jill J tonight” is in close or in a spatial neighboring location to the identified key “call”). Thus Lee teaches and discloses the argued limitations, i.e., “identifying the key in the digital representation of the handwritten text from among a plurality of predefined candidate keys, wherein identifying the key comprises determining that handwritten content is located within a predefined key region mapped to the predetermined action”.
Lastly, with respect to the amended limitations to claim 15, Lee teaches “causing execution of the predetermined action associated with the identified key, the execution of the predetermined action using the relevant handwritten content (Lee, Figure 17, Box 1716, pp [194]: activating an action responsive the identified key; Figure 19, Box 1914, pp [198]: performing an action responsive to the identified key), wherein identifying the key comprises determining that handwritten content is located within a predefined key region, and detecting the key symbol within the predefined key region (Lee, Figure 7, pp [107]-[109]: the content “Jill J tonight” is in close or in a spatial neighboring location to the identified key “call”). Thus Lee teaches and discloses the argued limitations, i.e., “causing execution of the predetermined action associated with the identified key, the execution of the predetermined action using the relevant handwritten content, wherein identifying the key comprises determining that handwritten content is located within a predefined key region, and detecting the key symbol within the predefined key region”.
As such, the argued features and limitations were written such that they read upon the cited reference Lee as explained in the above.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Publication No. US 2019/0339861) and further in view of Kompalli et al. (Publication No. US 2012/0026081).
Regarding claim 1. (Currently Amended) Lee teaches a handwriting parser configured to perform computer processes (Lee, the Abstract), comprising:
receiving a digital representation of handwritten text (Lee, Figure 4, pp [81], [84]), the handwritten text including:
(1) a key associated with a predetermined action (Lee, Figure 4, pp [81], [84], [146]: recognizing words, symbols), and (2) other handwritten content, wherein the key includes a symbol (Lee, Figure 4, pp [81], [84], [89], [99], [122], [146]);
identifying the key in the digital representation of the handwritten text from among a plurality of predefined candidate keys (Lee, Figure 7, pp [107]-[109]);
determining at least a portion of the other handwritten content that relates to the identified key, the at least a portion of the other handwritten content that relates to the identified key defining relevant handwritten content, wherein determining the portion of the other handwritten content that relates to the identified key comprises identifying handwritten content positioned within a spatial threshold relative to the identified key, wherein the spatial threshold is determined at least in part based on a relative dimension of the key (Lee, Figure 7, pp [107]-[109]);
causing execution of the predetermined action associated with the identified key, the execution of the predetermined action using the relevant handwritten content (Lee, Figure 17, Box 1716, pp [194]; Figure 19, Box 1914, pp [198]).
Lee teaches “receiving a digital representation of handwritten text” (Lee, Figure 4, pp [81], [84]). Lee, however, does not teach “handwritten text on paper after capturing an image of the paper”.
Kompalli teaches “handwritten text on paper after capturing an image of the paper” (Kompalli, the Abstract, Fig. 1, pp [19]-[23]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the affective filing date of the claimed invention was made to modify Lee by incorporating teachings of Kompalli, method and system for capturing and recognizing handwritten texts such as annotations and imaged contents on paper for identifying handwritten commands or pointed data from the handwritten annotations and imaged contents in order to import the extracted commands or the pointed data for further computer application executions, thus the system and method provide the improved technique to capture handwritten annotations and imaged contents on paper for feeding these captured information into a computerized system for quick and sufficient processing of the captured information in the most effective and reliable manner over conventional systems.
Regarding claim 13. (Currently Amended) Lee teaches a method of causing execution of a digital action based on handwritten text (Lee, the Abstract), the method comprising:
receiving a digital representation of handwritten text the handwritten text (Lee, Figure 4, pp [81], [84]), including:
(1) a key associated with a predetermined action (Lee, Figure 4, pp [81], [84]), and (2) other handwritten content (Lee, Figure 4, pp [81], [84]);
identifying the key in the digital representation of the handwritten text from among a plurality of predefined candidate keys, wherein identifying the key comprises determining that handwritten content is located within a predefined key region mapped to the predetermined action (Lee, Figure 7, pp [107]-[109]);
determining at least a portion of the other handwritten content that relates to the identified key, the at least a portion of the other handwritten content that relates to the identified key defining relevant handwritten content (Lee, Figure 7, pp [107]-[109]);
causing execution of the predetermined action associated with the identified key, the execution of the predetermined action using the relevant handwritten content (Lee, Figure 17, Box 1716, pp [194]; Figure 19, Box 1914, pp [198]).
Lee does not teach “wherein receiving the digital representation comprises capturing an image of the handwritten text using a camera of a mobile device.”.
Kompalli teaches “wherein receiving the digital representation comprises capturing an image of the handwritten text using a camera of a mobile device.” (Kompalli, Fig. 1, pp [19]-[23], [30]-[31]; Fig. 8, pp [52]-[54]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the affective filing date of the claimed invention was made to modify Lee by incorporating teachings of Kompalli, method and system for capturing and recognizing handwritten texts using a camera for obtaining annotations and imaged contents on paper for identifying handwritten commands or pointed data from the handwritten annotations and imaged contents in order to import the extracted commands or the pointed data for further computer application executions, thus the system and method provide the improved technique to capture handwritten annotations and imaged contents on paper for feeding these captured information into a computerized system for quick and sufficient processing of the captured information in the most effective and reliable manner over conventional systems.
Regarding claim 15. (Currently Amended) Lee teaches a tangible, non-transitory computer readable medium having stored thereon computer instructions which, when run on a computer processor, cause the computer processor to perform computer processes implementing a handwriting parser configured to perform computer processes (Lee, the Abstract), comprising:
receiving a digital representation of handwritten text the handwritten text (Lee, Figure 4, pp [81], [84]), including:
(1) a key associated with a predetermined action (Lee, Figure 4, pp [81], [84]), and (2) other handwritten content (Lee, Figure 4, pp [81], [84]);
identifying the key in the digital representation of the handwritten text from among a plurality of predefined candidate keys (Lee, Figure 7, pp [107]-[109]);
determining at least a portion of the other handwritten content that relates to the identified key, the at least a portion of the other handwritten content that relates to the identified key defining relevant handwritten content (Lee, Figure 7, pp [107]-[109]);
causing execution of the predetermined action associated with the identified key, the execution of the predetermined action using the relevant handwritten content, wherein identifying the key comprises determining that handwritten content is located within a predefined key region, and detecting the key symbol within the predefined key region (Lee, Figure 17, Box 1716, pp [194]; Figure 19, Box 1914, pp [198]).
Lee does not teach “handwritten text on paper”.
Kompalli teaches “handwritten text on paper” (Kompalli, the Abstract, Fig. 1, pp [19]-[23]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the affective filing date of the claimed invention was made to modify Lee by incorporating teachings of Kompalli, method and system for capturing and recognizing handwritten texts such as annotations and imaged contents on paper for identifying handwritten commands or pointed data from the handwritten annotations and imaged contents in order to import the extracted commands or the pointed data for further computer application executions, thus the system and method provide the improved technique to capture handwritten annotations and imaged contents on paper for feeding these captured information into a computerized system for quick and sufficient processing of the captured information in the most effective and reliable manner over conventional systems.
Regarding claim 2. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 1, wherein identifying the key comprises:
identifying the key based on a position of the key in the digital representation (Lee, Figure 15, pp [174], [181], [183]-[184]).
Regarding claim 3. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 1, wherein identifying the key comprises:
identifying a key candidate in the digital representation (Lee, Figure 15, pp [174], [181], [183]-[184]); accessing an alternate key table including a plurality of key candidates (Lee, Figure 15, pp [174], [181], [183]-[184]); and accessing a valid key table to identify the key from among the plurality of key candidates (Lee, Figure 15, pp [174], [181], [183]-[184]).
Regarding claim 4. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 3, wherein the alternate key table comprises, for each of the plurality of key candidates, a predetermined confidence metric (Lee, pp [118], Figure 9, pp [121]-[124], [126]-[128]).
Regarding claim 5. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 4, wherein accessing the valid key table to identify the key from among the plurality of key candidates comprises:
selecting a key candidate from among the plurality of key candidates based on the predetermined confidence metrics; and comparing the selected key candidate to valid keys in the valid key table (Lee, Figure 11, pp [135]-[136]).
Regarding claim 6. (Previously Presented) Lee, as modified by Kompalli, teaches the handwriting parser of claim 1, wherein determining at least a portion of the other handwritten content that relates to the identified key is a function of spacing information, and wherein processing the digital representation comprises processing the digital representation using the spacing information (Lee, Figure 4, pp [81], [84]; and Figure 7, pp [107]-[109]).
Regarding claim 7. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 3, further comprising:
generating the alternate key table from an alternate character map specifying, for each of a number of possible characters, at least one possible alternate character and a corresponding confidence metric (Lee, pp [118], Figure 9, pp [121]-[124], [126]-[128]).
Regarding claim 8. (Previously Presented) Lee, as modified by Kompalli, teaches the handwriting parser of claim 1, wherein obtaining the digital representation comprises:
processing an image of a writing surface having the handwritten text using an optical character recognition engine configured to convert the handwritten text into a digital representation (Lee, Figs. 1 and 4, input capture devices 104 capture handwritten text from the user on an input surface 106).
Regarding claim 9. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 8, wherein obtaining the digital representation comprises:
capturing the image using a camera of a mobile device (Lee, pp [43], [45], [205]).
Regarding claim 10. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 9, wherein obtaining the digital representation comprises:
receiving the handwriting on a touch screen (Lee, pp [42], [117], [205]).
Regarding claim 11. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 1, wherein the predetermined action is creating a to-do list (Lee, Figure 9, pp [121]-[124]).
Regarding claim 12. (Original) Lee, as modified by Kompalli, teaches the handwriting parser of claim 1, wherein the predetermined action triggers a purchase on an online marketplace (Lee, Figure 12, pp [145]-[148]).
Regarding claim 14. (Original) Lee, as modified by Kompalli, teaches the method of claim 13, wherein the key comprises a predetermined set of one or more characters (Lee, Figure 11, pp [135]-[136]).
Regarding claim 16. (Previously Presented) Lee, as modified by Kompalli, teaches the computer readable medium of claim 15, wherein the key comprises a predetermined set of one or more characters (Lee, Figure 11, pp [135]-[136]).
Claim(s) 21-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Publication No. US 2019/0339861), in view of Kompalli et al. (Publication No. US 2012/0026081) and further in view of Sekendur (Publication No. US 2002/0118181).
Regarding claim 21. (Previously Presented) Lee, as modified by Kompalli, teaches the handwriting parser of claim 1, wherein at least one of:
the key includes at least one symbol that identifies a set of one or more characters in the handwritten text as being a key (Lee, Fig. 4, pp [84], [186]);
the key is a user-customized key (Lee, pp [59], [69], [98]-[100]; Fig. 3, pp [116]);
the key is associated with metadata that defines one or more valid data fields associated with the key, wherein the metadata is used to determine the at least a portion of the other handwritten content that relates to the identified key defining relevant handwritten content (Lee, pp [160]-[161]); or
the user is requested to verify the action before causing execution of the action, optionally wherein the user verification is used as feedback to improve the accuracy of future optical character recognition processing (Lee, Fig. 15, pp [178]-[180]; Fig. 16, pp [186]-[188]).
Lee, as modified by Kompalli, does not teach “the handwritten text is written on synthetic paper.”
Sekendur teaches “the handwritten text is written on synthetic paper” (Sekendur, Fig. 1, pp [11]-[12], [46]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the affective filing date of the claimed invention was made to modify Lee and Kompalli, by incorporating teachings of Sekendur, method and system for detecting user’s handwriting texts on different surfaces including paper, synthetic paper, plastic, etc., and using a computer for analysis of the handwriting texts and converting the outputting to a keyboard typed representations from the handwriting texts, thus the method provides a significant improved advantage of using different surfaces for collecting handwriting texts by different writing mechanisms, e.g., stylus, ordinary pen/pencil, and using a computer for analyzing the handwriting texts to convert into keyboard typed texts thus to present a nice and easy to read version and therefore improving clarity of reading handwriting texts at a prompt and accurate manner.
Regarding claim 22. (Previously Presented) Lee, as modified by Kompalli, teaches the method of claim 13, wherein at least one of:
the key includes at least one symbol that identifies a set of one or more characters in the handwritten text as being a key (Lee, Fig. 4, pp [84], [186]);
the key is a user-customized key (Lee, pp [59], [69], [98]-[100]; Fig. 3, pp [116]);
the key is associated with metadata that defines one or more valid data fields associated with the key, wherein the metadata is used to determine the at least a portion of the other handwritten content that relates to the identified key defining relevant handwritten content (Lee, pp [160]-[161]); or
the user is requested to verify the action before causing execution of the action, optionally wherein the user verification is used as feedback to improve the accuracy of future optical character recognition processing (Lee, Fig. 15, pp [178]-[180]; Fig. 16, pp [186]-[188]).
Lee, as modified by Kompalli, does not teach “the handwritten text is written on synthetic paper.”
Sekendur teaches “the handwritten text is written on synthetic paper” (Sekendur, Fig. 1, pp [11]-[12], [46]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the affective filing date of the claimed invention was made to modify Lee and Kompalli, by incorporating teachings of Sekendur, method and system for detecting user’s handwriting texts on different surfaces including paper, synthetic paper, plastic, etc., and using a computer for analysis of the handwriting texts and converting the outputting to a keyboard typed representations from the handwriting texts, thus the method provides a significant improved advantage of using different surfaces for collecting handwriting texts by different writing mechanisms, e.g., stylus, ordinary pen/pencil, and using a computer for analyzing the handwriting texts to convert into keyboard typed texts thus to present a nice and easy to read version and therefore improving clarity of reading handwriting texts at a prompt and accurate manner.
Regarding claim 23. (Previously Presented) Lee, as modified by Kompalli, teaches the computer readable medium of claim 15, wherein at least one of:
the key includes at least one symbol that identifies a set of one or more characters in the handwritten text as being a key (Lee, Fig. 4, pp [84], [186]);
the key is a user-customized key (Lee, pp [59], [69], [98]-[100]; Fig. 3, pp [116]);
the key is associated with metadata that defines one or more valid data fields associated with the key, wherein the metadata is used to determine the at least a portion of the other handwritten content that relates to the identified key defining relevant handwritten content (Lee, pp [160]-[161]); or
the user is requested to verify the action before causing execution of the action, optionally wherein the user verification is used as feedback to improve the accuracy of future optical character recognition processing (Lee, Fig. 15, pp [178]-[180]; Fig. 16, pp [186]-[188]).
Lee, as modified by Kompalli, does not teach “the handwritten text is written on synthetic paper.”
Sekendur teaches “the handwritten text is written on synthetic paper” (Sekendur, Fig. 1, pp [11]-[12], [46]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the affective filing date of the claimed invention was made to modify Lee and Kompalli, by incorporating teachings of Sekendur, method and system for detecting user’s handwriting texts on different surfaces including paper, synthetic paper, plastic, etc., and using a computer for analysis of the handwriting texts and converting the outputting to a keyboard typed representations from the handwriting texts, thus the method provides a significant improved advantage of using different surfaces for collecting handwriting texts by different writing mechanisms, e.g., stylus, ordinary pen/pencil, and using a computer for analyzing the handwriting texts to convert into keyboard typed texts thus to present a nice and easy to read version and therefore improving clarity of reading handwriting texts at a prompt and accurate manner.
Conclusion
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/HUY C HO/Primary Examiner, Art Unit 2644