Adaptive Region Editing Tool for Image Boundary Sharpness

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Solution Overview

Problem

Current image editing techniques for selective region editing, such as background removal, are either too complex and time-consuming for manual methods or rely on user-defined clipping paths, which can result in undesirable effects like blurring or loss of sharpness.

Innovation Solution

An adaptive region editing tool that samples pixel properties within different subdivisions of a tool impression to determine property distributions, classifying these into edit classes to apply specific editing effects, allowing for intelligent guidance from user input and reducing manual effort.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If manual pixel-by-pixel editing is used, then editing precision can be controlled, but editing time and complexity increase significantly

Engineering Contradiction:

Improveediting precisionVSAvoidediting time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system automatically performs the editing operation by analyzing pixel properties and applying edits based on computed distributions, eliminating the need for manual pixel-by-pixel control while maintaining precision through automated algorithms

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system changes the approach from manual pixel control to automated parameter-based editing by computing property distributions and applying edits based on these distributions, significantly reducing time while maintaining precision

Inventive Principle:

Principle #35Parameter changes

2Extent of automation

If clipping path approach is used, then editing automation improves, but boundary sharpness decreases due to blending

Engineering Contradiction:

Improveediting automationVSAvoidboundary sharpness

Core Design Contradiction:

Extent of automationVSManufacturing precision

Solution Approach 1:

The system applies different editing treatments to different regions based on their spatial location and pixel property distributions, allowing sharp boundaries in critical areas while maintaining automation throughout the entire image

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The tool impression is divided into multiple spatially located subdivisions, each analyzed separately to compute property distributions, enabling precise control over boundary regions while maintaining overall automation

Inventive Principle:

Principle #1Segmentation

3Extent of automation

If existing automated blending techniques are used, then automation level increases, but user input utilization remains insufficient

Engineering Contradiction:

Improveautomation levelVSAvoiduser input utilization

Core Design Contradiction:

Extent of automationVSEase of operation

Solution Approach 1:

The system analyzes pixel properties within the tool impression to compute property distributions and uses this feedback to automatically determine edit classes and apply appropriate edits, fully utilizing user input placement for automated decision-making

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS7826668B1Adaptive region editing tool

Publication Date: 2010.11.02 8324450 DELAWARE

AI summary

Properties of pixels of a digital image are sampled within different subdivisions of an editing tool impression to produce different property distributions. The subdivisions may be differently-located within the tool impression. The property distributions from each region are classified to identify different edit classes within the property space, which are then used to apply an edit effect to the digital image within the tool impression. The edit classes may be represented by an edit profile in two or more dimensions (e.g., applying to one or more pixel properties).