Document Image Data Validation via OCR and Rule-Based Matching

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Solution Overview

Problem

The process of determining the quality of title policies for real property transfers is laborious due to the lack of electronic searching systems in many jurisdictions, requiring manual inspection of documents, which is time-consuming and inefficient.

Innovation Solution

A system and method for extracting data from document images by selecting document classifications, applying relevant rules to identify and validate data elements such as grantor and grantee names, property addresses, and legal descriptions, using Optical Character Recognition (OCR) and comparison with a database of target data elements, and storing validated data with associated coordinates.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual inspection of documents is used to determine title policy quality, then data extraction can be performed, but the process is time-consuming and laborious

Engineering Contradiction:

Improvedata extraction accuracyVSAvoidtitle examination time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical inspection process with an automated optical character recognition (OCR) system that captures document images and extracts text data electronically. This substitution eliminates the need for manual reading and transcription while maintaining data extraction accuracy through systematic image processing and pattern recognition algorithms.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary validation system that compares extracted data against known patterns, rules, and reference information. This intermediary layer verifies the accuracy of OCR extraction by checking for logical consistency, format compliance, and cross-referencing with property record databases, thereby maintaining precision while enabling automated processing.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If electronic searching systems are implemented for property records, then search efficiency is improved, but the system complexity and cost of creation increase

Engineering Contradiction:

Improvesearch efficiencyVSAvoidelectronic system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the electronic property record system into modular functional components: image capture module, OCR text extraction module, data validation module, and database storage module. Each component performs a specific function and can be independently developed, tested, and maintained. This segmentation reduces overall system complexity while enabling efficient property record searching through specialized processing at each stage.

Inventive Principle:

Principle #1Segmentation

3Reliability

If data validation is performed on extracted property records, then data accuracy is improved, but the processing time increases

Engineering Contradiction:

Improvedata accuracyVSAvoidprocessing speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent implements partial validation by applying different levels of checking to different data elements. Critical fields such as property addresses, legal descriptions, and party names undergo rigorous validation against multiple criteria, while less critical fields receive simpler format checking. This selective validation approach maintains high data accuracy for essential information while minimizing the overall processing time impact.

Inventive Principle:

Principle #16Partial or excessive action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach enables efficient and accurate extraction and validation of property record data, reducing the time and effort required for title examinations and improving the robustness of electronic property record search systems.

Implementation Method 1

using Optical Character Recognition (OCR) and comparison with a database of target data elements

Methodology Applied

Scientific EffectOptical Character Recognition: Photoelectric Effect

Data Source

PatentUS8064703B2Property record document data validation systems and methods

Publication Date: 2011.11.22 FIRST AMERICAN DATA TREE LLC

AI summary

A method of extracting data from a document image includes selecting a document classification for the document image that includes text. The classification is selected from a plurality of predetermined document classifications based on recognized text. The method also includes selecting rules from a database of rules based on the document classification. The rules define data elements to be populated based on recognized document text. The method also includes selecting target data elements from a database of data elements based on the selected document classification and the selected rules. The method also includes recognizing selected portions of the document image. The selected portions are determined by the selected rules. Recognizing selected portions of the document image generates one or more character strings based on recognized text. The method further includes comparing a specific character string to a target data element, thereby producing a match measure based on the comparison. The method also includes creating validated data based on the character string and the match measure and storing the validated data as a data element.