Fabric Defect Detection: 4-Point System, Image Processing & AI-Based Quality Control
- ALPER DIKTAS
- Aug 18
- 2 min read
Updated: 5 days ago
Fabric defect detection is a critical process in the textile industry to improve production quality and meet export standards. Even the smallest fabric defects can lead to order returns or high costs. Therefore, automated fabric defect detection systems provide manufacturers with both quality assurance and cost advantages.
Fabric Defect Detection Using the 4-Point System
The 4-Point System is a widely used, easy-to-understand, and measurable method in textile quality control.
Up to 3 inches defect: 1 point
3–6 inches: 2 points
6–9 inches: 3 points
Over 9 inches: 4 points
Using this scoring method, the total defect score per 100 yards of fabric is calculated. Typically, fabrics with a score below 40 points are considered “acceptable.
Automated Fabric Defect Detection with Image Processing
Traditional inspections rely on human eyesight, while image processing systems scan fabric using high-resolution cameras and analyze texture, color, shape, and pattern details.
This technology:
Detects defects faster and more accurately,
Reduces human error,
Enables 24/7 operation.
New Era in Defect Detection with Artificial Intelligence: Serkon.AI
Serkon.AI is an AI-powered fabric defect detection system. It not only identifies defects but also predicts quality, optimizes processes, and generates reports.
Key Features:
Autonomous Defect Detection: Real-time identification and reporting
Transition Module: Analyzes color variations and lot-based inconsistencies
Vertical/Horizontal Defect Detection: Categorizes defects based on position
User-Friendly Interface: Easy to use, quick onboarding
Self-Learning Algorithms: System improves with continuous use
How These Systems Work Together
The 4-Point System provides the measurement standard.
Image processing automates this standard.
Serkon.AI optimizes the process using artificial intelligence.
As a result, fabric defect detection becomes:
Faster
More consistent
More cost-effective
Application Scenario
A textile producer manufactures 10,000 meters of fabric per day. Before integrating Serkon.AI, manual inspection covered 400 meters per hour. After implementation, inspection speed increased to 1,200 meters per hour with a 97% accuracy rate.
Conclusion
Fabric defect detection is no longer a manual task—it has evolved into a data-driven, learning, and continuously improving system. Serkon.AI brings the future of quality control to today's production lines.
Contact us now and request your personalized demo presentation from Serkon.AI.
