Automated Pet Eye Correction via Abnormal Pupil Detection
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Solution Overview
Problem
Manual red-eye removal in digital images is inconvenient for users, as it requires manual selection and desaturation of eye regions, which is time-consuming and inefficient.
Innovation Solution
An automated method in electronic devices with image processors and sensors that detect pet faces, locate candidate eye regions, verify abnormal pupil regions, and correct them using a combination of classifiers and neural networks to recover abnormal pupil regions without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual red-eye removal is performed by user selection and desaturation, then color correction can be achieved, but user convenience deteriorates and processing time increases
Solution Approach 1:
The system automatically detects pet faces, locates eye regions, identifies abnormal pupil colors, and performs correction without user intervention. The electronic device serves itself by implementing the entire red-eye removal process autonomously through image processing algorithms, eliminating the need for manual user operations while maintaining correction accuracy
Solution Approach 2:
The manual mechanical process of user selection and color adjustment is replaced by automated image processing algorithms. The system uses computer vision techniques to detect and analyze eye regions, and applies digital signal processing to correct abnormal colors, substituting human manual operations with automated computational methods
2Manufacturing precision
If manual red-eye removal is performed, then color correction can be achieved, but processing speed deteriorates
Solution Approach 1:
The system performs preliminary detection of pet faces and eye regions before correction is needed. By pre-identifying target areas and abnormal colors through automated algorithms, the system prepares the image data for rapid correction, eliminating the need for slow manual selection processes while maintaining accurate color correction results
3Ease of operation
If automated detection and correction is implemented, then user convenience and processing speed improve, but device complexity increases
Solution Approach 1:
The image processing system integrates multiple functions into a unified automated workflow: pet face detection, eye region localization, abnormal color identification, and correction execution. By making the system multi-functional and self-contained, it handles the entire red-eye removal process through a single automated mechanism, reducing the need for separate manual operations and external tools
Data Source
AI summary
A method of performing eye correction is performed in an electronic device having an image processor, an image sensor, and a storage device. The image sensor captures image data, detects a pet face in the image data, and locates a plurality of candidate eye regions in the pet face. A classifier of the image processor verifies at least one eye region of the plurality of candidate eye regions, and the image processor recovers an abnormal pupil region of the at least one verified eye region.