Carpet Texture Measurement Through Depth-Map Defect Detection
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Solution Overview
Problem
Human inspectors face challenges with manual visual inspection in textile manufacturing, including low speed, high cost, inability to perform real-time inspection, and subjective perception leading to inconsistent product quality. Existing computer vision technologies are not equipped to address the variety of potential defects in textiles.
Innovation Solution
The system obtains an image of a textile portion, compares it to a reference image, determines areas indicative of height variations, and performs actions based on these determinations. This involves using cameras to capture images, converting them into depth maps, and comparing them to reference topographic maps to identify defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual visual inspection by human inspectors is used, then inspection can be performed with simple equipment, but inspection speed is low and cost is high
Solution Approach 1:
The patent replaces manual visual inspection with an automated image processing system that uses cameras to capture images of textile surfaces and computer vision algorithms to analyze them. The system captures multiple images at different angles and processes them to detect defects such as height variations, eliminating the need for human inspectors while maintaining equipment simplicity.
Solution Approach 2:
The system creates digital copies (images) of the textile surface at multiple angles and uses these copies for analysis. By comparing images captured from different perspectives, the system can detect defects without physical contact or complex measurement equipment, enabling high-speed inspection through computational analysis of visual data.
2Reliability
If manual visual inspection is used, then equipment cost is low, but inspection is not real-time and multiple inspectors are required
Solution Approach 1:
The image processing system operates continuously as textiles pass through the inspection area, capturing images at multiple angles without interruption. The automated analysis processes images immediately, providing real-time defect detection that maintains consistent product quality across all inspections without requiring multiple inspectors or breaking down inspection batches.
Solution Approach 2:
The system compares captured images against reference images and provides immediate feedback on defect detection. This feedback mechanism ensures consistent defect identification across different inspections and locations, eliminating the variability inherent in manual inspection by multiple human inspectors while maintaining real-time operation.
3Measurement precision
If human inspectors perform visual inspection, then subjectivity can be minimized through training, but different inspectors reach different conclusions on identical samples
Solution Approach 1:
The patent replaces subjective human judgment with objective computer vision algorithms that consistently apply the same analysis criteria to all textile samples. The automated system processes images through standardized computational methods, eliminating the variability in human perception and ensuring identical, repeatable defect detection results across all inspections.
Solution Approach 2:
By creating and comparing digital copies of textile surfaces at multiple angles, the system provides an objective, reproducible basis for defect detection. The digital images and their automated analysis eliminate the subjectivity of human visual inspection, ensuring that identical samples are evaluated consistently regardless of which inspector performs the inspection.
4Adaptability or versatility
If multiple inspectors are involved in approving textiles across multiple shifts and facilities, then inspection coverage can be broad, but product consistency becomes extremely difficult to obtain
Solution Approach 1:
The automated image processing system provides universal inspection capability that can be deployed across multiple facilities and shifts without requiring different inspectors. The same camera system, reference images, and analysis algorithms operate consistently at all locations, enabling broad inspection coverage while maintaining uniform defect detection standards and product quality across all facilities and time periods.
Data Source
AI summary
Methods and systems are disclosed for analyzing one or more images of a textile to determine a presence or absence of defects. In one example, an image of at least a portion of a textile may be obtained and compared to a reference image of a reference textile. Based on the comparison, one or more areas indicative of a height variation between the textile and the reference textile may be determined. An action may be performed based on the one or more areas indicative of the height variation.