Discriminatory Projection of Camouflaged Texture Through Line Masks


Nagappa Bhajantri, Pradeep Kumar R, Nagabhushan P, Journal of Information Processing Systems Vol. 9, No. 4, pp. 660-677, Dec. 2013  

https://doi.org/10.3745/JIPS.2013.9.4.660
Keywords: Camouflage, Line Mask, Enhancement, Texture analysis, Distribution pattern, histogram, Regression line
Fulltext:

Abstract

The blending of defective texture with the ambiencee texture results in camouflage. The gray value or color distribution pattern of the camouflaged images fails to reflect considerable deviations between the camouflaged object and the sublimating background demands improved strategies for texture analysis. In this research, we propose the implementation of an initial enhancement of the image that employs line masks, which could result in a better discrimination of the camouflaged portion. Finally, the gray value distribution patterns are analyzed in the enhanced image, to fix the camouflaged portions.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.




Cite this article
[APA Style]
Bhajantri, N., R, P., & P, N. (2013). Discriminatory Projection of Camouflaged Texture Through Line Masks. Journal of Information Processing Systems, 9(4), 660-677. DOI: 10.3745/JIPS.2013.9.4.660.

[IEEE Style]
N. Bhajantri, P. K. R, N. P, "Discriminatory Projection of Camouflaged Texture Through Line Masks," Journal of Information Processing Systems, vol. 9, no. 4, pp. 660-677, 2013. DOI: 10.3745/JIPS.2013.9.4.660.

[ACM Style]
Nagappa Bhajantri, Pradeep Kumar R, and Nagabhushan P. 2013. Discriminatory Projection of Camouflaged Texture Through Line Masks. Journal of Information Processing Systems, 9, 4, (2013), 660-677. DOI: 10.3745/JIPS.2013.9.4.660.