Many vision-based approaches for obstacle detection often state that vertical thin structure is of importance, e.g. poles and trees. However, there are also problem in detecting thin horizontal structures. In an industrial case there are horizontal objects, e.g. cables and fork lifts, and slanting objects, e.g. ladders, that also has to be detected. This paper focuses on the problem to detect thin horizontal structures. We introduce a test apparatus for testing thin objects as a complement for the test pieces for human safety described in the European standard EN 1525 Safety of industrial trucks – Driverless trucks and their systems. The system uses three cameras, situated as a horizontal pair and a vertical pair, which makes it possible to also detect thin horizontal structures. A sparse disparity map based on edges and a dense disparity map is used to identify problems with a trinocular system. Both methods use the Sum of Absolute Difference to compute the disparity maps. Tests show that the proposed trinocular system detects all objects at the test apparatus. If a sparse or dense method is used is not critical. Further work will implement the algorithm in real time and verify it on a final system in many types of scenery.