We present a simple ellipse detector that accurately extracts the parameters of an ellipse based on randomized Hough transform (RHT). Ellipse detection by the conventional RHT method is challenging due to the huge calculation burden and voting complexity for the five parameters of one ellipse. To address this, we extracted formulas that separated these five parameters into two to three parameters and proposed a separated two-level voting scheme based on the RHT. The original image was first processed by edge detection, eight-zone distribution of its direction, and edge lists merging, and then the parameters were calculated and voted by the separated two-level voting scheme. Finally, an evaluation method was used to determine whether or not the detected ellipse existed in the image. We tested our method on various kinds of real images, and the experiments demonstrated that the proposed method provided a precise and efficient ellipse detection.