Fabric Fault Detection System Through Image Processing
Textile is one of the major industries in Pakistan, responsible for the production of fabric. The automatic fabric fault detection system is required to reduce the cost and wastage of time. Quality inspection is a major aspect of modern industrial manufacturing process. In textile industry, fa
2025-06-28 16:32:30 - Adil Khan
Fabric Fault Detection System Through Image Processing
Project Area of Specialization Electrical/Electronic EngineeringProject SummaryTextile is one of the major industries in Pakistan, responsible for the production of fabric. The automatic fabric fault detection system is required to reduce the cost and wastage of time. Quality inspection is a major aspect of modern industrial manufacturing process. In textile industry, fabric inspection is important to maintain the fabric quality. This inspection can be further improved by applying image processing techniques. The algorithms are implemented using Raspberry Pi as main controller thus, reduce the size of the embedded hardware. The system is responsible to assess the quality of the fabric using implemented image processing algorithms on the capturing video of the rolling fabric. The piece of fabric that is not fulfilling the quality benchmark would be marked as faulty. This marking is done by a robotic arm connected with the Raspberry Pi.
Project ObjectivesThe objectives of our project are to
- Increase the effectiveness of quality inspection.
- To reduce the human effort and increase the assessment consistency.
- To produce high quality fabric.
- Increase the reliability of product.
Automated fabric fault detection system deals with fabric defects such as hole, torn, scratch, stretch, dirty spot, cracked point, misprints, or discoloration in clothing that makes the pattern inconsistent with the fabric design.Fault detection in patterned fabrics is a difficult task, so this system may be able to detect faults in both plain and patterned clothing.
The system consists of a central controller i.e. Raspberry Pi, which is further connected to a high resolution camera and a robotic arm. The camera is responsible to send the video of the rolling fabric to the main controller where image processing algorithms evaluate the video for possible fault(s) in the fabric. If there is any occurrence of the fault, the robotic arm would mark the piece of fabric as faulty. The process would be fast enough to respond in time so that only the piece of fabric contains the fault would be marked.
Benefits of the Project- As compared to the previous projects, this project requires less hardware that makes it handy and portable.
- Increased production with less human intervention.
- Increased quality in fabrics making the products reliable and acceptable by the consumer, hence winning the competition.
- Automated system using raspberry pi as a central controller to detect faults within fabric
- High resolution camera unit to capture the video in real-time.
- Indication of faults by stamping using robotic arm.
- The core technology implemented is Digital Image Processing on OpenCV.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 60020 | |||
| Raspberry PI | Equipment | 1 | 10000 | 10000 |
| Power supply | Equipment | 1 | 2000 | 2000 |
| Motors | Equipment | 6 | 670 | 4020 |
| Mechanical Structure | Equipment | 1 | 10000 | 10000 |
| Camera Unit | Equipment | 1 | 5000 | 5000 |
| Robotic arm | Equipment | 1 | 8000 | 8000 |
| SD card | Equipment | 1 | 500 | 500 |
| HDMI cable | Equipment | 1 | 500 | 500 |
| Screen | Equipment | 1 | 10000 | 10000 |
| Miscellaneous | Miscellaneous | 1 | 10000 | 10000 |