A new unsupervised algorithm for texture segmentation is proposed in this paper. The new scheme is based on the idea that texture features change abruptly near boundaries between different textures, and the segmentation can be carried out by detecting the feature changes or so-called feature edges. In this algorithm, the image is first projected onto a hyperplane called the characteristic image, in which the value of each pixel is not a grey level but a vector value of the local textural features. An edge detection algorithm is then extended to the vector space and applied to the hyperplane to detect the feature edges. In this way, textural boundaries in the image are detected. The validity of our algorithm is also confirmed by experimental results.