The Hough transform is a robust method for detecting discontinuous patterns in noisy images. When it is applied to the detection of a straight line, represented by the normal parameters, the transform provides only the length of the normal and the angle it makes with the axis. The transform gives no information about the length or the end points of the line. A few authors have suggested algorithms or the determination of the length and the end points of a line. The suggested methods are iterative in nature and are highly compute bound, thereby making them unsuitable for real-time applications. In this paper, we propose an efficient non-iterative algorithm to determine the coordinates of the end points, the length, and the normal parameters of a straight line using the Hough transform. The proposed algorithm is based on an analysis of the spread of votes in the accumulator array cells, representing orientations which are different from that of the line under consideration. The algorithm uses a coarse resolution accumulator array which reduces the computation time.