Feature extraction and clarity expression are two main problems in 3D flow visualization research. To solve these problems, a feature extracting based 3D streamline placement algorithm is presented. The algorithm ensures that the feature structures around the critical points can be described correctly, and the output result shares good clarity. The algorithm is comprised of three processes. Firstly, based on the fast detection of critical points, the critical points are classified according to the eigenvalues of their Jacobian Matirx，and the match between the critical points and the seed templates is performed. Secondly, the seeds points are ordered in priority, and streamlines are generated in physical space. Finally, in image space, the distance between streamlines is controlled by the preset threshold value, and the nearest streamline to the observer is held according to the depth detection, thus the display clarity is ensured.