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Proceedings Paper

Scene sketch generation using mixture of gradient kernels and adaptive thresholding
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Paper Abstract

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.

Paper Details

Date Published: 20 April 2016
PDF: 6 pages
Proc. SPIE 9845, Optical Pattern Recognition XXVII, 98450N (20 April 2016); doi: 10.1117/12.2226032
Show Author Affiliations
Sidike Paheding, Univ. of Dayton (United States)
Almabrok Essa, Univ. of Dayton (United States)
Vijayan Asari, Univ. of Dayton (United States)

Published in SPIE Proceedings Vol. 9845:
Optical Pattern Recognition XXVII
David Casasent; Mohammad S. Alam, Editor(s)

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