The Beamlet transform is an efficient tool for multi-scale analysis. A new edge detection algorithm is proposed through improving the algorithm of linear feature extraction based on Beamlet transform. A definition of weighted average for the gray values on a Beamlet is proposed

all dyadic squares of an image are searched for edge in all directions of Beamlets. The evaluation of this algorithm is taken from several aspects

such as the continuity of the edge detection

the antinoise performance and so on. The algorithm is applied to detect edge and identify lane from road images. The experiments show that the continuity of edge detection is good

the new method has low rate of wrong detection and miss detection

which also has good performance on line extraction. But the performance of antinoise is inferior and the calculation has low speed. The edge we gained contains information on the position

the orientation and so on

which will be convenient for the target recognition.