This paper presents a novel algorithm for unsupervised texture segmentation. We incorporate a set of texture features under a segmentation framework, based on the active contour without edges model with level set representation and a connected component filtering strategy. The experiments performed show that, it can be used for segmentation of multiple-textured images, with a segmentation quality that achieves up to 96% of average using our own quantitatively image quality measure, which allows the comparison between the segmented image versus its ground truth image.