Paper
28 May 2015 Shape distance transform for morphological filtering and landing site selection
Author Affiliations +
Abstract
Morphological filtering, erosion and dilation on images, has been successfully applied to many image processing and pattern recognition fields. Landing site selection on the other hand, finding the best (safest) point to land with given obstacle distributions and aircraft shapes, has significant value for landing aircraft in tight environments. In this paper, we derive shape distance transform theory, and using this theory, we build a connection between morphological filtering and landing site selection which are traditionally treated as two different topics. From shape distance transform theory, we show that morphological filtering and land site selection can be implemented by shape distance transform. Thus, fast shape distance transform will provide fast implementation of morphological filtering and landing site selection. For convex polygon shape templates, we propose propagation techniques to compute shape distance transform. Then we introduce a new approach for faster morphological filtering and landing site selection. This new approach is independent of template sizes and its computational complexity is 0(1) which is much lower than 0(N) of the direct implementation, where N is the number of pixels in templates. For large templates, N is large, and the new approach is significantly faster than the direct implementation
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bing C. Li "Shape distance transform for morphological filtering and landing site selection", Proc. SPIE 9476, Automatic Target Recognition XXV, 94760B (28 May 2015); https://doi.org/10.1117/12.2182513
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KEYWORDS
Image filtering

Binary data

Transform theory

Image processing

Computer vision technology

Machine vision

Optimal filtering

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