Image Processing Apparatus Chromatic Marker Region Classification

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Solution Overview

Problem

Existing image processing technologies require manual labor to classify marker regions on documents of unknown format and are prone to errors in recognizing symbol characters, necessitating the use of multiple markers and labor-intensive processes.

Innovation Solution

An image processing apparatus that detects and classifies highlighted and circled regions using a chromatic marker, allowing for automatic classification and processing of marker regions without the need for multiple markers, by employing a processor to analyze RGB image data, remove noise, and determine the type of marker region based on chromatic color detection and contour analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual classification of marker regions is performed on documents of unknown format, then classification accuracy can be maintained, but labor intensity increases significantly

Engineering Contradiction:
Improveclassification accuracyVSAvoidlabor time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system performs automatic classification of marker regions by detecting chromatic colors and analyzing contour patterns, eliminating the need for manual classification while maintaining accuracy through algorithmic analysis of highlight and circle patterns

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

Manual classification operations are replaced by an automated image processing system that uses chromatic color detection and contour analysis algorithms to identify and classify marker regions based on their visual patterns

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If symbol characters are written in marker regions for recognition, then region identification is possible, but error rate increases and user labor is required

Engineering Contradiction:
Improveregion identification accuracyVSAvoiduser labor time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The system automatically identifies marker regions through chromatic color detection and contour pattern recognition without requiring users to write symbol characters, eliminating the labor and error-prone nature of manual symbol entry

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system uses chromatic color detection to identify marker regions, leveraging the color properties of highlighters and markers to automatically distinguish marked regions from unmarked areas without requiring additional symbolic input

Inventive Principle:
Principle #32Color changes

3Adaptability or versatility

If multiple markers are used to differentiate marker region types, then classification capability is improved, but device complexity increases

Engineering Contradiction:
Improvemarker region classification capabilityVSAvoidmarker system complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system uses chromatic color detection to differentiate between various marker region types, analyzing color properties and contour patterns to classify regions as highlights, circles, or other patterns without requiring multiple physical markers

Inventive Principle:
Principle #32Color changes

Solution Approach 2:

The system segments marker regions based on their visual characteristics such as contour patterns and color properties, automatically classifying different region types through pattern recognition rather than requiring distinct marker types

Inventive Principle:
Principle #1Segmentation

4Measurement precision

If coordinates are designated for each original document to classify marker regions, then classification precision is maintained, but ease of operation deteriorates

Engineering Contradiction:
Improvemarker region classification precisionVSAvoiddocument processing convenience
Core Design Contradiction:
Measurement precisionVSEase of operation

Solution Approach 1:

The system automatically performs marker region classification by detecting chromatic colors and analyzing contour patterns in the scanned document image, eliminating the need for users to manually designate coordinates for each document

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system performs automatic classification based on visual pattern recognition of marker regions, pre-establishing classification rules that work across documents of any format without requiring document-specific coordinate setup

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentEP3489859B1Image processing apparatus
Publication Date: 2023.02.08 TOSHIBA TEC KK
  • EP3489859B1 patent drawingFigure 1
  • EP3489859B1 patent drawingFigure 2~3
  • EP3489859B1 patent drawingFigure 4~8

AI summary

According to one embodiment, an image processing apparatus includes a scanner, a memory, and a processor. The scanner acquires a read image of an original document. The memory stores the read image of the original document that is acquired by the scanner. The processor detects a highlighted region including a region that is highlighted with a chromatic color in the read image of the original document which is stored in the memory and a circled region including a region circled by the chromatic color, and classifies the highlighted region as a region for first processing and classifies the circled region as a region for second processing.