Image Processing Apparatus Region Division for High-Resolution Printing

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Solution Overview

Problem

Existing image processing methods, such as error diffusion, face inefficiencies in processing large high-resolution images due to dependency relationships between pixels, leading to increased processing time and memory constraints, and limitations in data division directions that hinder parallel processing and sequential printing.

Innovation Solution

An image processing method that divides image data into non-processing and processing regions based on grayscale values, allowing for batch processing and simultaneous halftoning across multiple regions, thereby reducing the need for continuous conversion and improving throughput by utilizing multiple digital signal processors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If error diffusion method is used to convert multi-grayscale image data into binarized print data, then printing quality is improved, but processing time increases significantly for large high-resolution images

Engineering Contradiction:

Improveprinting qualityVSAvoidprocessing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent divides the image data into multiple regions based on grayscale value thresholds, creating processing regions that require error diffusion and non-processing regions that do not. This segmentation allows parallel processing of different regions, reducing overall processing time while maintaining printing quality in the processing regions.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies different processing methods to different regions of the image data. Processing regions use error diffusion for high quality printing, while non-processing regions use simpler conversion methods. This local differentiation optimizes both quality and speed by applying intensive processing only where necessary.

Inventive Principle:

Principle #3Local quality

2Quantity of substance

If image data is divided into allowable size for memory processing, then processing capability is improved, but dependency relationship in data processing becomes limited and parallel processing is restricted

Engineering Contradiction:

Improvememory space utilizationVSAvoiddata processing throughput

Core Design Contradiction:

Quantity of substanceVSProductivity

Solution Approach 1:

The patent segments the image data into processing regions and non-processing regions based on grayscale value distributions. This segmentation enables independent processing of each region, allowing parallel execution and improving throughput while working within memory constraints.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a new dimension for data division by using grayscale value thresholds to create regions, rather than only dividing by spatial dimensions. This allows error diffusion to proceed in multiple directions simultaneously, improving parallel processing capability.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Productivity

If image data is divided in a specific direction to enable parallel processing, then processing throughput is improved, but dependency relationship in data processing becomes direction-dependent and printing flexibility is reduced

Engineering Contradiction:

Improvedata processing throughputVSAvoidprinting direction flexibility

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent creates regions based on grayscale value thresholds rather than fixed spatial directions. This segmentation approach allows error diffusion to proceed in multiple directions from each region boundary, maintaining printing flexibility while enabling parallel processing.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent allows different error diffusion directions at different region boundaries based on the local grayscale value distribution. This local adaptation enables optimal processing directions for each region while maintaining overall printing flexibility.

Inventive Principle:

Principle #3Local quality

4Manufacturing precision

If sequential conversion processing is performed to maintain dependency relationships, then data conversion accuracy is improved, but processing time increases for large images

Engineering Contradiction:

Improvedata conversion accuracyVSAvoidprocessing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent segments the image into processing regions that maintain dependency relationships for accurate error diffusion and non-processing regions that can be processed independently. This allows parallel processing while maintaining accuracy in regions where it is most important.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent identifies and processes non-processing regions first, where error diffusion is not needed, before processing regions that require sequential error diffusion. This preliminary action reduces the overall processing time by completing independent conversions early.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10110778B2Image processing method, image processing apparatus, image processing program, and printing system

Publication Date: 2018.10.23 SEIKO EPSON CORP

AI summary

An image processing method in which image data including a grayscale value in each pixel is converted into print data including formation necessity of dots, includes extracting a region in which a total value of the grayscale value of the pixel included in each predetermined division in which the image data is divided does not become a predetermined threshold value as a non-processing region; and extracting a region surrounded with the non-processing region as a processing region.