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Robust building roof segmentation using airborne point cloud data

- Gilani, Syed, Awrangjeb, Mohammad, Lu, Guojun

  • Authors: Gilani, Syed , Awrangjeb, Mohammad , Lu, Guojun
  • Date: 2016
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 23rd IEEE International Conference on Image Processing, ICIP 2016; Phoenix, United States; 25th-28th September 2016; published in Proceedings - International Conferenec on Image Processing, ICIP Vol. 2016-August, p. 859-863
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  • Description: Approximation of the geometric features is an essential step in point cloud segmentation and surface reconstruction. Often, the planar surfaces are estimated using principal component analysis (PCA), which is sensitive to noise and smooths the sharp features. Hence, the segmentation results into unreliable reconstructed surfaces. This article presents a point cloud segmentation method for building detection and roof plane extraction. It uses PCA for saliency feature estimation including surface curvature and point normal. However, the point normals around the anisotropic surfaces are approximated using a consistent isotropic sub-neighbourhood by Low-Rank Subspace with prior Knowledge (LRSCPK). The developed segmentation technique is tested using two real-world samples and two benchmark datasets. Per-object and per-area completeness and correctness results indicate the robustness of the approach and the quality of the reconstructed surfaces and extracted buildings. © 2016 IEEE.
  • Description: Proceedings - International Conference on Image Processing, ICIP

PAWN: a payload‐based mutual authentication scheme for wireless sensor networks

- Jan, Mian, Nanda, Priyadarsi, Usman, Muhammad, He, Xiangjian

  • Authors: Jan, Mian , Nanda, Priyadarsi , Usman, Muhammad , He, Xiangjian
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Concurrency and computation Vol. 29, no. 17 (2017), p. e3986-n/a
  • Full Text: false
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  • Description: Summary Wireless sensor networks (WSNs) consist of resource‐starving miniature sensor nodes deployed in a remote and hostile environment. These networks operate on small batteries for days, months, and even years depending on the requirements of monitored applications. The battery‐powered operation and inaccessible human terrains make it practically infeasible to recharge the nodes unless some energy‐scavenging techniques are used. These networks experience threats at various layers and, as such, are vulnerable to a wide range of attacks. The resource‐constrained nature of sensor nodes, inaccessible human terrains, and error‐prone communication links make it obligatory to design lightweight but robust and secured schemes for these networks. In view of these limitations, we aim to design an extremely lightweight payload‐based mutual authentication scheme for a cluster‐based hierarchical WSN. The proposed scheme, also known as payload‐based mutual authentication for WSNs, operates in 2 steps. First, an optimal percentage of cluster heads is elected, authenticated, and allowed to communicate with neighboring nodes. Second, each cluster head, in a role of server, authenticates the nearby nodes for cluster formation. We validate our proposed scheme using various simulation metrics that outperform the existing schemes.
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