Paper
9 December 2004 Measurement of the length of pedestrian crossings from image data
Mohammad Shorif Uddin, Tadayoshi Shioyama
Author Affiliations +
Abstract
A computer vision based new method for the measurement of the length of pedestrian crossings using a single camera is described. The main objective of this research is to develop a travel aid for the blind people. In a crossing, the usual black road surface is painted with constant width periodic white bands. In Japan, this width is 45 cm. The crossing region as well as its length is detected using this concept. At first, the crossing direction is determined from the power spectrum using fast Fourier transform. The periodic white and black bands are detected using integration along the crossing direction and then differentiation of the integral data perpendicular to crossing. This detection may be erroneous due to adverse effects of the neighboring region of crossing, as the intensity of the whole image is used for bands detection. To remove the neighboring effects, the crossing region is extracted. Then the crossing bands are detected from the image intensity using the crossing region only. Experiment is performed using 32 real road scenes with pedestrian crossing. The rms error is found 2.28 m. The technique determines the crossing length with good accuracy for crossings marked clearly with white paintings as well as fine image resolution.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohammad Shorif Uddin and Tadayoshi Shioyama "Measurement of the length of pedestrian crossings from image data", Proc. SPIE 5578, Photonics North 2004: Photonic Applications in Astronomy, Biomedicine, Imaging, Materials Processing, and Education, (9 December 2004); https://doi.org/10.1117/12.567168
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Cameras

Roads

Error analysis

Image resolution

Computer vision technology

Data integration

Machine vision

Back to Top