After improvement of the traditional phase-grouping baseline algorith m and k-means clustering algorithm,this paper proposes a new algorithm to detect man-made objects in hi gh-resolution remote sensing optical images,which is based on the difference of geometric shape between man -made objects and natural ones. First,an improved phase-grouping method is employed to extract lines in the image efficiently;Then,the center points of extracted-lines are treated as processing objects and the lines are c lassified into k classes by k-m eans clustering algorithm;Finally,man-made objects are picked up based on the numb er of the lines and the geometric elements in every class.The experimental results show that the method proposed in this paper is valid for detection of man-made objects with the detection precision above 90%,and so on,and the detection speed reaches 10frames persecond to the image with 512pixels×512pixels.