Image Processing Apparatus Neutral Color Hue Preservation

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing image processing technologies often alter the hue of images during processing, particularly when neutral colors are involved, leading to unintended changes in image quality and hue distortion.

Innovation Solution

An image processing system that replaces the color value of target pixels with the candidate color closest to the original pixel value, maintaining the image hue by classifying pixels into attributes such as background, dark, and neutral colors, and adjusting color values accordingly in the YCbCr color space.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If binarization is performed using intermediate density between image section and show-through section as threshold value, then show-through objects are removed from image data, but neutral color objects are also removed causing hue distortion

Engineering Contradiction:
Improveshow-through removal accuracyVSAvoidhue accuracy
Core Design Contradiction:
ReliabilityVSManufacturing precision

Solution Approach 1:

The patent segments the image processing by applying different treatments to different pixel types. Neutral color pixels are processed differently from show-through pixels through hue information comparison, allowing selective removal of show-through while preserving neutral color objects.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by preserving hue information specifically for neutral color pixels while removing show-through pixels. This localized approach ensures that only the necessary portions are modified, maintaining overall image quality and accurate color representation.

Inventive Principle:
Principle #3Local quality

2Stability of the object's composition

If representative color is replaced by pure color in flat color region, then color uniformity is improved, but hue accuracy significantly changes

Engineering Contradiction:
Improvecolor uniformityVSAvoidhue accuracy
Core Design Contradiction:
Stability of the object's compositionVSManufacturing precision

Solution Approach 1:

The patent changes parameters by selectively replacing representative colors with pure colors only in specific conditions. By controlling when and where color replacement occurs, the system maintains color uniformity where needed while preserving hue accuracy where important.

Inventive Principle:
Principle #35Parameter changes

3Ease of operation

If uniform image processing is applied to neutral color objects, then processing consistency is improved, but hue distortion significantly changes

Engineering Contradiction:
Improveprocessing consistencyVSAvoidhue accuracy
Core Design Contradiction:
Ease of operationVSManufacturing precision

Solution Approach 1:

The patent applies different processing quality to different regions. Neutral color pixels receive specialized processing that preserves their hue information, while other pixels receive standard processing. This localized approach maintains both consistency and accuracy.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The processing is segmented into different pathways: neutral color pixels are identified and processed to preserve hue, while show-through pixels are removed. This segmentation allows consistent processing within each category while maintaining overall hue accuracy.

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP3096294B1Computer program, image processing apparatus, and method for improving quality of image data
Publication Date: 2019.07.24 BROTHER KOGYO KK
  • EP3096294B1 patent drawingFigure 1
  • EP3096294B1 patent drawingFigure 2
  • EP3096294B1 patent drawingFigure 3

AI summary

A CPU (21) of a PC (2) identifies a first attribute pixel, which is a pixel having a color value included in a color range of a background color (step S63). The CPU identifies a second attribute pixel, which is a pixel having a color value included in a dark color range (step S57). The CPU registers, in a three-dimensional table, a per block average that represents color values of a plurality of pixels included in a divided block, as a posterization candidate color (step S93). The CPU replaces a color value of a third attribute pixel with a target color, which is the posterization candidate color closest to the color value of the third attribute pixel (step S111).