Object Boundary Transformation for Automatic Image Replacement

Solution Overview

Problem

Manual labeling of objects in scene images is a time-consuming and costly process that fails to meet individual user needs.

Innovation Solution

An image processing method that performs line detection on object boundaries, generates a transformed area based on reference lines and exterior angle bisectors, and overlays a preset image to replace the object in the scene image.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual labeling is used to replace objects in scene images, then personalized user requirements can be met, but time consumption and costs increase significantly

Engineering Contradiction:

Improvepersonalized user requirementsVSAvoidtime consumption

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system enables automatic object replacement by having the computer execute algorithms that automatically detect object boundaries, generate transformed areas, and overlay replacement images without human intervention. The processor autonomously performs line detection, calculates geometric transformations, and composes final images, eliminating the need for manual labeling while meeting personalized requirements through programmable automation

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual process of object labeling with an automated computational system. Instead of human operators manually identifying and replacing objects, the system uses line detection algorithms, coordinate transformation mathematics, and automated image processing to achieve the same result, substituting mechanical human labor with computational automation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If manual labeling is used to replace objects in scene images, then personalized user requirements can be met, but costs increase significantly

Engineering Contradiction:

Improvepersonalized user requirementsVSAvoidcosts

Core Design Contradiction:

Adaptability or versatilityVSEase of manufacture

Solution Approach 1:

The system enables automatic object replacement by having the computer execute algorithms that automatically detect object boundaries, generate transformed areas, and overlay replacement images without human intervention. The processor autonomously performs line detection, calculates geometric transformations, and composes final images, eliminating the need for manual labeling while meeting personalized requirements through programmable automation

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual process of object labeling with an automated computational system. Instead of human operators manually identifying and replacing objects, the system uses line detection algorithms, coordinate transformation mathematics, and automated image processing to achieve the same result, substituting mechanical human labor with computational automation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If automatic object replacement is implemented, then manual workload is reduced, but processing complexity increases

Engineering Contradiction:

Improvemanual workload reductionVSAvoidprocessing complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent divides the complex object replacement task into distinct sequential steps: line detection to identify object boundaries, minimum bounding rectangle generation to define the object extent, transformed area calculation to determine replacement region geometry, and image overlay to compose the final result. This segmentation of the processing pipeline manages complexity by breaking down the overall task into manageable, modular operations that can be executed systematically

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces intermediate computational structures to bridge different processing stages. The minimum bounding rectangle serves as an intermediary that simplifies the complex object boundary into a standardized form. The transformed area acts as an intermediary coordinate system that maps the replacement image to the target region. These intermediary representations simplify the overall processing by providing standardized intermediate forms that ease the transition between detection and final composition stages

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12586147B2Image processing method and image processing apparatus for transforming objects within an image

Publication Date: 2026.03.24 BEIJING WODONG TIANJUN INFORMATION TECH CO LTD

AI summary

The present disclosure provides an image processing method and an image processing apparatus. The image processing method including: performing line detection on a boundary of an object in a scene image to obtain a plurality of candidate lines; taking one of the plurality of the candidate lines, which has the largest number of pixels overlapping with the boundary, as a first reference line; generating a minimum bounding rectangle of the object in the scene image; generating a transformed area, wherein each of four vertexes of the minimum bounding rectangle is on one of four sidelines of the transformed area; transforming a preset image into the transformed area to generate a transformed image; and overlaying the object with the transformed image to update the scene image.