Identity Photo Image Processing for Defect Detection and Color Correction
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Solution Overview
Problem
Existing methods for obtaining identity photos, such as those required for identity verification, often result in low success rates due to strict requirements and the need for specific environments and postures, leading to inefficient and costly processes.
Innovation Solution
An image processing method that includes detecting photographing defects and color deviations in images, performing color correction when necessary, and generating target images based on corrected originals, allowing users to capture images anywhere without fixed environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users take photos at fixed locations (photo studios or self-service machines) to meet identity photo requirements, then the photo quality and verification success rate improve, but the process becomes cumbersome and less convenient
Solution Approach 1:
The system performs automatic photographing defect detection and color correction processing without requiring users to visit photo studios or use self-service machines. The device itself provides the correction services, enabling users to take photos conveniently anywhere while maintaining verification success rates through automated quality improvement.
Solution Approach 2:
The system detects photographing defects (such as lighting conditions, background, posture) and automatically adjusts image parameters through color correction processing. This transforms images that initially do not meet identity photo requirements into qualified images, resolving the contradiction between convenient photographing and verification success rate.
2Reliability
If color correction is performed on all original images, then the quality of target images improves, but unnecessary computational efforts are wasted on images that already pass quality checks
Solution Approach 1:
The system performs photographing defect detection before color correction processing. This preliminary check identifies images that already meet quality requirements, allowing the system to skip unnecessary color correction steps and avoid wasting computational resources while ensuring quality images receive appropriate processing.
Solution Approach 2:
Instead of applying color correction to all images uniformly, the system applies correction only to images that fail the photographing defect detection. This partial action approach optimizes resource usage by performing corrections only when necessary, balancing quality improvement with computational efficiency.
Data Source
AI summary
Disclosed are an image processing method and apparatus, a computer device and a storage medium, which relate to the field of artificial Intelligence. The method includes receiving an original image; performing image photographing defect detection and color deviation detection on the original image, the image photographing defect detection determining whether there exists a photographing defect that is irreparable through image processing, the color deviation detection determining whether there exists color cast in the original image; performing color correction on the original image if the original image passes the image photographing defect detection and does not pass the color deviation detection; and generating a target image based on the color-corrected original image.