A review on the color segmentation with emphasis on the point clouds

9 pages•Published: November 4, 2019

Abstract

Currently, there are technologies such as Unmanned Aerial Vehicles (UAV) that allow more efficient field work in geology. With the capture of aerial photographs and their processing with algorithms based in Structure from Motion (SfM), it is possible to obtain a position XYZ with their RGB color. The resulting outputs, whether images or point clouds, can be used to recognize patterns of geological layer in stratified walls from color. This semi-automatic segmentation allows to identify subtle changes between lithologies through the transformation of RGB to other color spaces such as CIELab.
The review was done around the issues of color segmentation identified through a search level scheme. These were color information, type of spatial data, segmentation methods and color spaces.

Keyphrases: 3d point cloud, color space, segmentation

In: Oscar S. Siordia, José Luis Silván Cárdenas, Alejandro Molina-Villegas, Gandhi Hernandez, Pablo Lopez-Ramirez, Rodrigo Tapia-McClung, Karime González Zuccolotto and Mario Chirinos Colunga (editors). Proceedings of the 1st International Conference on Geospatial Information Sciences, vol 13, pages 105-113.

Links:	https://easychair.org/publications/paper/ZKdp
	https://doi.org/10.29007/sthw

BibTeX entry

@inproceedings{iGISc2019:review_color_segmentation_with,
  author    = {Sergio Macías-Medrano},
  title     = {A review on the color segmentation with emphasis on the point clouds},
  booktitle = {Proceedings of the 1st International Conference on Geospatial Information Sciences},
  editor    = {Oscar S. Siordia and José Luis Silván Cárdenas and Alejandro Molina-Villegas and Gandhi Hernandez and Pablo Lopez-Ramirez and Rodrigo Tapia-McClung and Karime González Zuccolotto and Mario Chirinos Colunga},
  series    = {Kalpa Publications in Computing},
  volume    = {13},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/ZKdp},
  doi       = {10.29007/sthw},
  pages     = {105-113},
  year      = {2019}}

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