An enhanced segmentation on vision-based shadow removal for vehicle detection

Chun Ting Chen, Chung Yen Su, Wen Chung Kao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Citations (Scopus)

Abstract

We present an enhanced segmentation method to reduce the interference of shadows for vehicle detection. The main advantage of the proposed method is its low-complexity. We use only the luminance of an image for shadow removal and keep the chrominance components of the image intact. The luminance of the current image is enhanced and each pixel is compared with a pixel-dependent threshold for locating shadow regions. With that, the shadow regions can be located more accurately and the moving objects can be extracted more completely. Experimental results verify the proposed approach and show that it is helpful for vehicle detection.

Original languageEnglish
Title of host publication1st International Conference on Green Circuits and Systems, ICGCS 2010
Pages679-682
Number of pages4
DOIs
Publication statusPublished - 2010 Sep 20
Event1st International Conference on Green Circuits and Systems, ICGCS 2010 - Shanghai, China
Duration: 2010 Jun 212010 Jun 23

Publication series

Name1st International Conference on Green Circuits and Systems, ICGCS 2010

Other

Other1st International Conference on Green Circuits and Systems, ICGCS 2010
CountryChina
CityShanghai
Period10/6/2110/6/23

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Keywords

  • Background subtraction
  • Digital image processing
  • Object detection
  • Shadow removal

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

Chen, C. T., Su, C. Y., & Kao, W. C. (2010). An enhanced segmentation on vision-based shadow removal for vehicle detection. In 1st International Conference on Green Circuits and Systems, ICGCS 2010 (pp. 679-682). [5542975] (1st International Conference on Green Circuits and Systems, ICGCS 2010). https://doi.org/10.1109/ICGCS.2010.5542975