3D Carpet Texture Inspection for Height Variation Defects
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Solution Overview
Problem
Human visual inspection for textile quality assurance is subjective, slow, costly, and limited in detecting defects, and existing computer vision technologies are inadequate for the variety of defects in textile manufacturing.
Innovation Solution
A system using 3D cameras and a decision engine to compare textile images with reference images, determining height variations and performing actions based on detected defects, including adjusting manufacturing processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human visual inspection is used for textile quality assurance, then cost and subjectivity are reduced, but inspection speed and consistency are improved
Solution Approach 1:
The patent replaces the mechanical human visual inspection system with an automated image processing system that uses cameras to capture textile images and computer algorithms to analyze defects. This substitution eliminates manual labor while maintaining objective, consistent evaluation criteria through digital image analysis.
Solution Approach 2:
The system creates digital copies (images) of the textile products and analyzes these copies rather than physically inspecting each product. Multiple images can be captured and analyzed simultaneously, enabling rapid throughput while maintaining consistent evaluation through algorithmic comparison against reference images.
2Measurement precision
If multiple inspectors compare textiles manually, then detection capability is improved, but cost and time consumption increase
Solution Approach 1:
The image processing system operates continuously without interruption, capturing and analyzing images at high speed as textiles move through the inspection zone. Multiple images are processed in parallel and sequentially, maintaining continuous detection capability without the start-stop nature of manual inspection cycles.
Solution Approach 2:
The system adds the dimension of digital image data analysis to traditional visual inspection. By converting visual information into digital images that can be processed by algorithms, the system enables simultaneous analysis of multiple defects, patterns, and characteristics that would require multiple human inspectors to detect manually.
3Adaptability or versatility
If human inspectors perform visual inspection, then flexibility in evaluation is maintained, but consistency and objectivity are reduced
Solution Approach 1:
The system uses adjustable image processing parameters and comparison thresholds that can be modified to adapt to different textile types, defect severities, and inspection standards. The algorithmic approach maintains consistent application of these parameters across all inspections, eliminating human variability while preserving adaptability through parameter configuration.
Solution Approach 2:
The system compares captured images against reference images and provides immediate feedback on defect detection, allowing for real-time adjustment of inspection criteria and thresholds. This feedback mechanism ensures consistent evaluation standards are applied uniformly across all inspected items while maintaining flexibility in adapting to different product specifications.
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.