DETECTING AND DISCARDING OF SHADOWS IN IMAGE USING GEOMETRIC CONTOURS AND REGION BASED SEGMENTATION USING THRESHOLDING APPROACH

Authors

  • Shanthi. S Department of Electronics and Communication Engineering, AVC College of Engineering, Annai College of Engineering & Technology, INDIA
  • Vinothini. K. R Department of Electronics and Communication Engineering, AVC College of Engineering, Annai College of Engineering & Technology, INDIA
  • R. Manikandan Department of Electronics and Communication Engineering, AVC College of Engineering, Annai College of Engineering & Technology, INDIA

DOI:

https://doi.org/10.29121/granthaalayah.v3.i2.2015.3036

Keywords:

Geometric Active Contours, Image Segmentation, Shadow Detection, Building Detection, Feature Extraction

Abstract [English]

Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances.In this paper, a new algorithm for shadow detection and isolation of buildings in high-resolution panchromatic satellite imagery is proposed. This algorithm is based on tailoring the traditional model of the geometric active contours such that the new model of the contours is systematically biased toward segmenting the shadow and the dark regions in the image. Feature extraction a type of dimensionality reduction that efficiently represents interesting parts of an image as a compact feature vector. This approach is useful when image sizes are large and a reduced feature representation is required to quickly complete tasks such as image matching and retrieval.

Downloads

Download data is not yet available.

References

Adeline .K. R. M, M. Chen, X. Briottet, S. K. Pang, and N. Paparoditis, “Shadow detection in very high spatial resolution aerial images: A comparative study,” ISPRS J. Photogramm Remote Sens., vol. 80, pp. 21–38, Jun. 2013. DOI: https://doi.org/10.1016/j.isprsjprs.2013.02.003

Al-Najdawi.N, H. E. Bez, J. Singhai, and E. A. Edirisinghe, “A survey of cast sshadow detection algorithms,” Pattern Recognit. Lett., vol. 33, no. 6, pp. 752–764, Apr. 2012. DOI: https://doi.org/10.1016/j.patrec.2011.12.013

Arbel.E and H. Hel-Or, “Shadow removal using intensity surfaces and texture anchor points,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33,no. 6, pp. 1202–1216, Jun. 2011.

Chung. K. L, Y. R. Lin, and Y. H. Huang, “Efficient shadow detection of color aerial images based on successive thresholding scheme,” IEEE Trans. Geosci. Remote Sens., vol. 47, no. 2, pp. 671–682, Feb. 2009. DOI: https://doi.org/10.1109/TGRS.2008.2004629

Guo.R, Q. Dai, and D. Hoiem, “Single-image shadow detection and removal using paired regions,” in Proc. CVPR, Jun. 20–25, 2011, pp. 2033–2040. DOI: https://doi.org/10.1109/CVPR.2011.5995725

Huang.X and L. Zhang, “Morphological building/shadow index for building extraction from high-resolution imagery over urban areas,” IEEE J.Sel. Topics. Appl. Earth Observ. Remote Sens., vol. 5, no. 1, pp. 161–172,Feb. 2012. DOI: https://doi.org/10.1109/JSTARS.2011.2168195

Liu.Z, K. Huang, and T. Tan, “Cast shadow removal in a hierarchical manner using MRF,” IEEE Trans. Circuits Syst. Video Tech., vol. 22, no. 1,pp. 56–66, Jan. 2012. DOI: https://doi.org/10.1109/TCSVT.2011.2158335

Downloads

Published

2015-02-28

How to Cite

S, S., K. R, V., & Manikandan. (2015). DETECTING AND DISCARDING OF SHADOWS IN IMAGE USING GEOMETRIC CONTOURS AND REGION BASED SEGMENTATION USING THRESHOLDING APPROACH. International Journal of Research -GRANTHAALAYAH, 3(2), 13–19. https://doi.org/10.29121/granthaalayah.v3.i2.2015.3036