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dc.contributor.authorChin-Teng Linen_US
dc.contributor.authorShi-An Chenen_US
dc.contributor.authorYing-Chang Chengen_US
dc.contributor.authorChao-Ting Hongen_US
dc.date.accessioned2014-12-08T15:24:46Z-
dc.date.available2014-12-08T15:24:46Z-
dc.date.issued2006en_US
dc.identifier.isbn978-1-4244-0099-7en_US
dc.identifier.issn1062-922Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/17224-
dc.identifier.urihttp://dx.doi.org/10.1109/ICSMC.2006.384993en_US
dc.description.abstractThe objective of this paper is to investigate a novel design for local motion vectors (LMVs) of image sequences, which are often used in a digital image stabilization (IS) system. The IS technique removes unwanted shaking phenomenon in image sequences captured by hand-held camcorders. It includes two main parts such as motion estimation and compensation. Most of computation power occurs in the part of motion estimation. In order to reduce this complexity, an idea, which integrates an adaptive-threshold method and cellular neural networks (CNN) architecture, is designed to improve this problem. The design only implements the most important local motion estimation with the array size of 19x25 pixels. Experimental results with HSPICE simulation and CNNUM are shown that the proposed architecture fast searches the location of possible LVMs and has the capability of real-time operations.en_US
dc.language.isoen_USen_US
dc.titleCNN-based local motion estimation for image stabilization processing and its implementationen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/ICSMC.2006.384993en_US
dc.identifier.journal2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGSen_US
dc.citation.spage1816en_US
dc.citation.epage1819en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000248078502005-
Appears in Collections:Conferences Paper


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