@inproceedings{da2ea950a1c6417fb7fd656fa20a9b6a,
title = "Automatic texture exemplar extraction based on a novel textureness metric",
abstract = "Traditional texture synthesis methods usually emphasized the final effect of the target textures. However, none of them focus on auto-extraction of the source texture exemplar. In this paper, we present a novel textureness metric based on Gist descriptor to accurately extract texture exemplar from an arbitrary image including texture regions. Our method emphasizes the importance of the exemplar for the example-based texture synthesis and focus on ideal texture exemplar auto-extraction. To improve the efficiency of the texture patch searching, we perform a Poisson disk sampling to crop exemplar randomly and uniformly from images. To improve the accuracy of texture recognition, we also use a SVM for the UIUC database to distinguish the texture regions and non-texture regions. The proposed method is evaluated on a variety of images with different kinds of textures. Convincing visual and statistics results demonstrated its effectiveness.",
keywords = "Synthesizability, Texture exemplar, Texture feature, Textureness",
author = "Huisi Wu and Junrong Jiang and Ping Li and Zhenkun Wen",
year = "2017",
month = sep,
doi = "10.1007/978-3-319-77383-4_78",
language = "English",
isbn = "9783319773827",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "798--806",
editor = "Bing Zeng and Hongliang Li and Qingming Huang and {El Saddik}, Abdulmotaleb and Shuqiang Jiang and Xiaopeng Fan",
booktitle = "Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers",
note = "18th Pacific-Rim Conference on Multimedia, PCM 2017 ; Conference date: 28-09-2017 Through 29-09-2017",
}