Analysis of image transfer mechanisms in a RESTful API client-server architecture and its application to lane detection

Luis Moron-Rodriguez, Bryan Longa-Chevarria, Pedro Shiguihara-Juarez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study investigates the effect of image rescaling and format changing hosted in a RESTful API architecture considering transfer time as a critical factor to apply lane detection on a external server. We employ Probabilistic Hough Transform to perform the detection because it is invariant to pixel position and robust to noise. Before being trasmitted to the external server, images are rescaled and their formats are changed, this way lane detection on the images can be performed faster than working with the original images. From the image formats used in the experiments, the JPG or JPEG yields the best results. When performing the rescaling and format change, transmission and processing time is halved.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Aerospace and Signals, INCAS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9781538632789
DOIs
StatePublished - 28 Nov 2017
Externally publishedYes
Event2017 IEEE International Conference on Aerospace and Signals, INCAS 2017 - Lima, Peru
Duration: 8 Nov 201710 Nov 2017

Publication series

NameProceedings of the 2017 IEEE International Conference on Aerospace and Signals, INCAS 2017
Volume2017-November

Conference

Conference2017 IEEE International Conference on Aerospace and Signals, INCAS 2017
Country/TerritoryPeru
CityLima
Period8/11/1710/11/17

Keywords

  • API
  • Client-server
  • Hough Transform
  • Image processing
  • Lane detection
  • RESTful

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