We present a high-speed method for triangular object detection. The proposed method utilizes the recently developed, real-time edge segment detection algorithm, Edge Drawing; hence, the name EDTriangles, which consists of a detection stage and a validation stage. In the detection stage, EDTriangles extracts edge segments from the image using Edge Drawing and converts these edge segments into line segments, which are then converted into line pairs according to the angles between the line segments and the distance between their endpoints. Next, the line pairs are combined together using some heuristics to generate many triangle candidates, some of which are valid detections and some invalid. Finally, in the validation stage the candidate triangles are validated using the Helmholtz principle and number of false alarms computation to eliminate false detections. Experimental results show that EDTriangles runs very fast, detects various types of triangular objects ranging from narrow to wide-angled triangles and offers a higher detection performance compared to some of the well-known triangle detection algorithms found in the literature.