Abstract: A two-step iris localization approach from coarse to fine is presented according to the distribution of the iris’s gray scale.After the iris image is segmented through the k-means clustering algorithm for threshold，the pupil region is isolated and the border of the pupil is located coarsely by using the geometric properties of the circle.Then Gauss filtering is used to reduce noise and Canny operator is used to detect inside and outside border.The result of rough localization is combined to reduce the blindness of search process，so both pupil border and iris border are extracted fast through Hough transform.Experiments show that this method can extract the boundary precisely and quickly，to meet the requirements of real-time.

Key words: iris localization, Hough transform, gray projection, k-means clustering

摘要： 针对虹膜的灰度分布特点，提出了一种粗定位和精定位相结合的虹膜定位算法。首先，通过k-mans聚类算法对图像进行动态阈值分割，分离出瞳孔区域，利用圆的几何特性进行粗定位；然后运用Gauss滤波降低噪声干扰和Canny算子进行边缘检测，结合粗定位的结果，应用Hough变换进行精定位，以快速提取虹膜内外边缘。实验表明，该方法能准确快速地定位虹膜的边界以满足实时性要求。

关键词: 虹膜定位, Hough变换, 灰度投影, k-means聚类