A Technique About Neural Network for Passageway Detection

  • Pedro Lucas de Brito
  • Félix Mora-Camino
  • Luiz Gustavo Miranda Pinto
  • José Renato Garcia Braga
  • Alexandre C. Brandão RamosEmail author
  • Hildebrando F. Castro Filho
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 800)


This article brings a proposal to implement a passageway detector for a drone, like windows, doors, holes etc. In this case, it was applied on the model Tello of Ryze Tech. The modeling technique uses a Neural Convolutional Deep Learning Network, with a pre-supervised training. This training is done with three image classes: unobstructed path, obstructed path, and the passageway inside of the path, to a specific environment, such as a school or a hospital. After the detection of a way defined by the user, the technique uses image filters to find a polygon through the window and compare the returned data with the values stored in the neural network dataset. To find the best parameters to identify the passage in the processing, the algorithm makes an adjustment through parameters interpolation that allows the drone to perceive its crossing for many cases of environmental variations. The Network model used is the SSD implemented on Google’s TensorFlow framework and for the image processing, it uses filters and functions from OpenCV library, where both codes are implemented in Python programming language.


Image processing Neural network Deep learning Supervised training Quadrotor Drone Passageway detection Way detection Window detection Door detection 



The authors would like to gratefully thank the founding institution CAPES.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Pedro Lucas de Brito
    • 1
  • Félix Mora-Camino
    • 2
  • Luiz Gustavo Miranda Pinto
    • 1
  • José Renato Garcia Braga
    • 3
  • Alexandre C. Brandão Ramos
    • 1
    Email author
  • Hildebrando F. Castro Filho
    • 4
  1. 1.Institute of Mathematics and ComputingFederal University of ItajubáItajubáBrazil
  2. 2.Federal Fluminense University, Brazil ComputingRio De JaneiroBrazil
  3. 3.Nacional Research Institute (INPE)São José dos CamposBrazil
  4. 4.Aeronautical Institute of Technology, Brazil ComputingRio De JaneiroBrazil

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