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A Hierarchical Horizon Detection Algorithm

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4 Author(s)
Yu-Fei Shen ; Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, USA ; Dean Krusienski ; Jiang Li ; Zia-ur Rahman

A hierarchical elastic computer-aided detection algorithm is proposed to automatically detect the horizon in an aerial image. A hierarchical strategy, including coarse-level detection and fine-level adjustment, is applied. First, the original image is blurred by a large-scale low-pass filter. Then, a Canny edge detector and Hough transform are successively utilized to find major edges in the image and identify lines associated with those major edges. The desired horizon is modeled by the resulting line that best satisfies certain criteria. By doing so, the general position of the horizon can be quickly detected at the coarse-level step. Since the horizon is often not a straight line, an elastic fine-level adjustment is applied to capture the precise curvature of the horizon. A quantitative performance metric is designed, and preliminary experimental results show the feasibility and reliability of the proposed algorithm.

Published in:

IEEE Geoscience and Remote Sensing Letters  (Volume:10 ,  Issue: 1 )