Autonomous robust helipad detection algorithm using computer vision

This paper presents the design and implementation of a Vision based Helipad detection algorithm in an aerial image by image processing techniques. The aerial image obtained from the on board camera of Unmanned Aerial Vehicle (UAV) was processed by several image processing techniques to remove the noise and to segment the helipad. Then this image was matched with a pre-loaded template of the Helipad by means of Point Feature Matching by Speeded up Robust Features (SURF) thereby detecting the Helipad in the aerial image. This method is successful in detecting the Helipad in an aerial image irrespective of its scale change or in-plane rotation. It is also robust to small amount of out-of-plane rotation and occlusion. The average helipad detection time was found to be 28ms. This technique can be incorporated in embedded systems of the UAV's for autonomously detecting the Helipad for landing. We have presented the results tested on MATLAB (Image Processing Toolbox) which demonstrates that this helipad detection algorithm is robust.

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