Obviousness

US patent 12125319 focuses on an electronic voting system utilizing Printed Vote Records (PVRs) where voter selections are recorded in voter-readable characters. The system uses Optical Character Recognition (OCR) on this voter-readable text to generate a cast vote record (CVR), emphasizing a "what you see is what you get" approach for voter transparency. A key inventive aspect involves verifying the OCR data against a second data set, typically an encoded barcode containing a digitally signed hash of the voter's selections, to ensure data accuracy and PVR integrity before the CVR is finalized and used for tabulation.

This analysis identifies combinations of prior art references that would have made the claimed invention obvious to a person having ordinary skill in the art (POSA) at the time of the invention (priority date: July 27, 2018).

Obviousness Combination: US20020072961A1 (McDermott) + US5850480A (Scan-Optics) + US20090256703A1 (Bolton)

1. Primary Reference: US20020072961A1 to McDermott ("Auto-verifying voting system and voting method")
McDermott describes an auto-verifying voting system that uses printed ballots and automatically counts votes from them. The system provides a "machine readable and human readable verifiable printed ballot". It further states that the system can "capture a human verifiable image of a marked ballot for comparison with the computer determined ballot markings" and that "the voter is allowed to vote using a paper ballot where the voter marks their selections on the paper ballot. The paper ballot is then scanned by a computer that reads the voter's selections. The voter can then verify that the computer properly read their selections". This reference clearly teaches:

• Generating a printed vote record (PVR) with voter-readable selections.
• Electronically capturing information from the PVR (scanning).
• A computer reading voter selections from the human-readable ballot, which inherently implies a form of character or mark recognition.
• The concept of a voter verifying that the computer accurately read their selections from the human-readable ballot, embodying the "what you see is what you get" principle.
• The system can "print a duplicate of the paper ballot, which contains a bar code that identifies the original ballot and any errors found on the original ballot," suggesting the use of encoded data for verification or error reporting.

2. Secondary Reference: US5850480A to Scan-Optics ("OCR error correction methods and apparatus utilizing contextual comparison")
Scan-Optics discloses methods for correcting OCR errors through "contextual comparison" and "dictionary matching". This patent teaches how to improve the accuracy and reliability of OCR processes by comparing recognized characters or strings to a known dictionary of valid terms.

• Motivation to combine with McDermott: A POSA seeking to implement or improve the "computer determined ballot markings" and "computer properly read their selections" functionality in McDermott's system would find it obvious to apply known OCR techniques, especially those with error correction capabilities. Given that McDermott's system relies on accurately reading human-readable selections, integrating Scan-Optics' OCR error correction methods, such as contextual comparison with an election dictionary, would directly enhance the accuracy and reliability of interpreting voter selections.

3. Tertiary Reference: US20090256703A1 to Bolton ("System and Method for Detecting Security Features on Paper Ballots")
Bolton describes systems and methods for detecting security features on paper ballots, including "printed images, watermarks, special inks, barcodes, or other machine-readable markings".

• Motivation to combine with McDermott and Scan-Optics: McDermott already suggests using barcodes for ballot identification and error reporting. A POSA concerned with election integrity and the possibility of tampering with paper ballots (especially after voter verification but before tabulation) would be motivated to use more robust security features. Incorporating a barcode containing a digitally signed hash of the voter's selections, as taught by Bolton, into McDermott's system would provide a strong integrity check. This barcode data could serve as a "second data set" for comparison with the OCR-generated "first data set" (from Scan-Optics' enhanced OCR) to confirm accuracy and detect alterations before generating the final cast vote record. This directly aligns with the verification steps in US12125319.

Obviousness Analysis of Claims (e.g., Claims 1, 15, 29, 34 of US12125319):

• Generating a printed vote record with voter-readable text: Taught by McDermott's "human readable verifiable printed ballot" where a voter marks selections.
• Electronically capturing information and using OCR on voter-readable text to generate a first data set: McDermott's scanning and computer reading of voter selections from the human-readable ballot, combined with Scan-Optics' well-known OCR techniques and error correction, makes this obvious. A POSA would understand that OCR is the standard method for a computer to "read" human-readable text.
• Electronically capturing second information (encoded data) and generating a second data set: McDermott refers to barcodes for identification and error reporting. Bolton explicitly teaches using barcodes as security features on paper ballots. It would be obvious to a POSA to use these barcodes to store encoded data, such as a hash of the vote selections, as a "second data set."
• Comparing the first data set (OCR) to the second data set (encoded data) to confirm accuracy: McDermott's emphasis on voter verification and the use of barcodes for error identification, coupled with Bolton's teaching of barcodes for security, would motivate a POSA to compare the OCR-derived selections with the securely encoded data (e.g., a hash in a barcode) to ensure the accuracy and integrity of the vote before it is cast.
• Generating a cast vote record based on the OCR data and confirming accuracy prior to generation: McDermott describes automatically counting votes from verified ballots. The act of confirming accuracy through the comparison of OCR data and the secure barcode hash (as established by the combination) before finalizing the CVR is an obvious safety and integrity measure for a voting system. Tabulating the election using this CVR, potentially before vote auditing, is a standard function of such systems.

Therefore, the combination of McDermott, Scan-Optics, and Bolton provides all the elements of US12125319. A POSA, motivated by the desire for enhanced accuracy, transparency, and security in electronic voting systems with paper trails, would have been led to combine these references in the manner claimed.