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.