Robust image retrieval for lacy and embroidered fabric

Image retrieval is a task which retrieves similar images from a large database based on a given input query image. The lacy and embroidered fabric contains repetitive patterns and rich texture, making the image retrieval difficult. The GIST feature is a spatial information feature that performs well on retrieving images with duplicate patterns. Speeded-up robust features (SURF) feature is invariant to rotation, which makes it powerful in retrieving rotated images. The method proposed in this paper is to combine the benefits of both GIST and SURF features, supporting the image retrieval from a fabric image database. In addition, we extract the structure from the texture via the relative total variation to eliminate the influence of complex texture on the feature point extraction. A key insight and contribution of our paper is that the combination enables accurate fabric image retrieval, especially for rotated images. To demonstrate the robustness and accuracy of our method, we applied it to a database that contains 527 fabric images. The experimental results show that the proposed algorithm outperforms the state-of-the-art methods on the fabric images with hollow and embroidery patterns.