Automated Image Coloring Using Learned Reference Models
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Solution Overview
Problem
Current methods for automatically coloring images using reference information are inefficient, as they require manual intervention and cannot handle large volumes of image data quickly, particularly in applications like animation and cartoon production where consistency across characters is needed.
Innovation Solution
An information processing apparatus and method that includes a target image data acquisition unit, area designation unit, reference information selection unit, and coloring processing unit, utilizing a learned model to automatically select and apply reference information for designated areas within image data, enabling efficient and consistent coloring across images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual coloring process is performed for each character while confirming reference information, then coloring consistency can be maintained, but the number of sheets that can be handled in a limited time is reduced
Solution Approach 1:
The patent replaces the manual mechanical coloring process with an automated image processing system that uses reference information to automatically determine coloring parameters. The system extracts features from reference images and applies them to target images through automated algorithms, eliminating the need for manual confirmation while maintaining consistent coloring results across multiple sheets.
Solution Approach 2:
The patent uses reference information (reference images) as templates to copy coloring patterns and parameters to target images. By extracting coloring features from reference images and applying them automatically to multiple target sheets, the system achieves consistent reproduction of coloring styles without manual intervention for each sheet.
2Productivity
If automated coloring process is implemented without reference information selection, then processing speed is improved, but coloring consistency and quality deteriorate
Solution Approach 1:
The patent performs preliminary selection and extraction of reference information before the actual coloring process. The system identifies and extracts relevant coloring parameters from reference images in advance, preparing them for automated application. This preliminary action ensures that the subsequent automated coloring process maintains high consistency while achieving fast processing speeds.
Solution Approach 2:
The patent introduces reference information as an intermediary between the automated processing system and the target images. The reference images serve as mediators that provide coloring guidelines and parameters, enabling the automated system to produce consistent results without manual intervention. The reference information bridges the gap between automated speed and quality consistency.
Data Source
AI summary
An information processing apparatus includes a memory and processing circuitry coupled to the memory. The processing circuitry is configured to acquire target image data to be subjected to coloring, designate an area to be subjected to coloring by using reference information in the target image data, determine reference information to be used for the designated area, and perform a coloring process on the designated area by using the determined reference information, based on a learned model for coloring which has been previously learned in the coloring process using the reference information.