Herringbone Fabric Symmetry Detection for Accurate Pattern Cutting
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Solution Overview
Problem
Existing methods for automatic cutting of herringbone fabrics struggle to accurately detect characteristic points of the pattern, requiring manual intervention and reducing productivity.
Innovation Solution
A method that automatically detects the position of lines passing through the tips of chevrons in herringbone fabrics by optimizing a symmetry criterion of two mirror sub-images acquired along predefined operation lines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection of characteristic points is used, then detection precision can be maintained, but productivity decreases and time consumption increases
Solution Approach 1:
The patent replaces manual mechanical detection with an automated image processing system. The system captures images of the fabric pattern and uses digital image processing algorithms to automatically detect characteristic points, eliminating the need for manual visual inspection and measurement while maintaining high precision through computational analysis.
Solution Approach 2:
The patent creates a digital copy of the fabric pattern through image capture. By working with a digital representation of the pattern rather than the physical fabric itself, the system enables automated analysis and detection of characteristic points, significantly improving productivity while maintaining detection accuracy through algorithmic processing.
2Productivity
If automated cutting is implemented without accurate pattern detection, then productivity increases, but manufacturing precision deteriorates
Solution Approach 1:
The patent performs pattern detection and characteristic point identification before the cutting process begins. By pre-processing the fabric pattern information and establishing a digital model with accurately detected characteristic points, the system ensures that subsequent automated cutting operations maintain high manufacturing precision while benefiting from automated productivity improvements.
Solution Approach 2:
The patent uses the detected characteristic points and pattern information as feedback to control the automated cutting system. The digital model created from image processing provides real-time guidance to the cutting mechanism, ensuring that cuts are made at precise locations that maintain pattern alignment and manufacturing quality throughout the automated process.
3Productivity
If image processing is used for pattern detection, then productivity increases and time consumption decreases, but device complexity increases
Solution Approach 1:
The patent employs an image processing system that serves multiple functions: capturing fabric pattern images, processing images to detect characteristic points, creating digital models, and guiding cutting operations. By using a single multi-functional system rather than separate dedicated devices for each task, the patent reduces overall device complexity while maintaining high productivity benefits from automation.
Data Source
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AI summary
The invention relates to a method and system for automatically detecting characteristic points of a herringbone fabric (T-A) with a view to automatically cutting pieces, the herringbone patterns being formed by V-shaped features with vertices that are aligned along a plurality of parallel axes, comprising a step of acquiring an image of a segment of the tissue, a step of initialising the detection comprising acquiring, on the basis of predefined parameters or on the basis of the image, geometric parameters of the herringbone patterns and defining lines of operation (Li) perpendicular to the axes (Kj) of the herringbone patterns, and a step of determining, in the image, coordinates of points of passage of axes of the herringbone patterns along lines of operation via the optimisation of a criterion of symmetry of two mirror sub-images acquired along lines of operation.