Translator Disclaimer
20 April 2016 Scene sketch generation using mixture of gradient kernels and adaptive thresholding
Author Affiliations +
This paper presents a simple but effective algorithm for scene sketch generation from input images. The proposed algorithm combines the edge magnitudes of directional Prewitt differential gradient kernels with Kirsch kernels at each pixel position, and then encodes them into an eight bit binary code which encompasses local edge and texture information. In this binary encoding step, relative variance is employed to determine the object shape in each local region. Using relative variance enables object sketch extraction totally adaptive to any shape structure. On the other hand, the proposed technique does not require any parameter to adjust output and it is robust to edge density and noise. Two standard databases are used to show the effectiveness of the proposed framework.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sidike Paheding, Almabrok Essa, and Vijayan Asari "Scene sketch generation using mixture of gradient kernels and adaptive thresholding", Proc. SPIE 9845, Optical Pattern Recognition XXVII, 98450N (20 April 2016);


Contour-based shape similarity
Proceedings of SPIE (October 02 1998)
Timed fast exact Euclidean distance (tFEED) maps
Proceedings of SPIE (February 25 2005)
Object-oriented representation of image space by puzzletrees
Proceedings of SPIE (November 01 1991)
Multicolor well-composed pictures
Proceedings of SPIE (January 04 1995)

Back to Top