Evaluation of fabric pilling grade based on visual saliency model

Abstract

In order to achieve the objectivity and accuracy of the evaluation of fabric pilling performance, a new objective evaluation of fabric pilling grade based on visual saliency model is proposed. First of all, the local feature saliency mechanism-Gaussian pyramid decomposition was used to achieve that pilling was separated from the uneven information of fabric texture and illumination. And the center-surround operation was used to obtain the saliency images of fabric pilling defects. Then the global feature saliency mechanism-spectral residual method was used to improve the saliency of fabric pilling defects, and mean structural similarity was used to evaluate the quality of fabric pilling saliency images. Finally, the fabric pilling interest images was obtained by Gaussian fitting threshold segmentation, and the pilling feature parameters were extracted for grade evaluation. The results show that the algorithm can enhance the pilling saliency and obtain effective pilling characteristic parameters, and realize the accurate evaluation of 1～5 fabric pilling grade.

Keywords

• fabric pilling
• gaussian pyramid decomposition
• spectral residual
• structural similarity
• center-surround operation
• threshold segmentation