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An automatic algorithm to extract accurate eyebrow contours in a human face image is proposed. Based on the extracted eye corners, upper eye boundaries and the position points of the eyebrows, a feature region is limited to a local searching area. Separating the local searching area into several sub-areas and performing K-means clustering in each sub-area, we can obtain a rough region for each eyebrow. The rough contour obtained by tracking the rough eyebrow region is defined as an initial snake. Then the accurate eyebrow contour can be extracted by our improved snake method. Some prior knowledge about the shape of the object is used in both clustering and the snake method. Lastly, an application using the extracted eyebrow contours for face recognition is presented. The experimental results show that our method can detect the eyebrow contours with high accuracy and the eyebrow contour is useful for face recognition.