The speedy development in electricity infrastructure due to urge in domestic and business usage requires a safe and secure maintenance of power line corridor (PLC) for the delivery of uninterrupted power supply to consumers. Inspection of PLC using light detection and ranging (LiDAR) has gain importance in the recent decade. In this paper, we have presented a new method for automatic extraction of wires from PLC using LiDAR point cloud data. Firstly, the pylons and vegetations around the PLC is removed by using their shape and area properties. Then, pylon locations are used to extract the wire points in the form of span between two consecutive pylons. These spans are divided into several segments such that each segment has slice of wires from span. A clustering algorithm based on the Euclidean distance is further used to separate wires which are at different height levels in each segment and the wire-count on each cluster is generated by defining the distance thresholds. Each clustered points are projected into a plane perpendicular to the direction of wires. Finally, wires are separated by fitting a 2D line and by using point and line distance formula. Results are presented on different spans from complex and semi-complex datasets with low point density. Experimental results show that the proposed method is able to extract the single or bundle wires with completeness and correctness of 99% and 100% respectively.