Real Time Fabric Defect Detection System on an Embedded DSP Platform
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Abstract (arXiv)
In industrial fabric productions, automated real time systems are needed to find out the minor defects. It will save the cost by not transporting defected products and also would help in making compmay image of quality fabrics by sending out only undefected products. A real time fabric defect detection system (FDDS), implementd on an embedded DSP platform is presented here. Textural features of fabric image are extracted based on gray level co-occurrence matrix (GLCM). A sliding window technique is used for defect detection where window moves over the whole image computing a textural energy from the GLCM of the fabric image. The energy values are compared to a reference and the deviations beyond a threshold are reported as defects and also visually represented by a window. The implementation is carried out on a TI TMS320DM642 platform and programmed using code composer studio software. The real time output of this implementation was shown on a monitor.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Sep 2014.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1.
4 papers.
- 2024A Novel Representation of Periodic Pattern and Its Application to Untrained Anomaly Detectioncited by 1
- 2022Convolutional neural networks and multi-threshold analysis for contamination detection in the apparel industrycited by 0
- 2023Broken Rail Detection With Texture Image Processing Using Two-Dimensional Gray Level Co-occurrence Matrixcited by 0
- 2025A Single Image Is All You Need: Zero-Shot Anomaly Localization Without Training Datacited by 0
- 2025A Single Image Is All You Need: Zero-Shot Anomaly Localization Without Training Data22 Sep 2025
- 2024A Novel Representation of Periodic Pattern and Its Application to Untrained Anomaly Detection9 Sep 2024
- 2023Broken Rail Detection With Texture Image Processing Using Two-Dimensional Gray Level Co-occurrence Matrix23 Apr 2023
- 2022Convolutional neural networks and multi-threshold analysis for contamination detection in the apparel industry26 Jul 2022