Reduction of syntactic video data clustering complexity in processing with compacted dither coding

Ranathunga, L. and Zainuddin, R. and Abdullah, N.A. (2008) Reduction of syntactic video data clustering complexity in processing with compacted dither coding. In: International Symposium on Information Technology, AUG 26-29, 2008 , Univ Kebangsaan, Fac Informat Sci & Technol, Kuala Lumpur, MALAYSIA .

Full text not available from this repository.
Official URL:


The growing consumption of the digital video information is significant in this era. The digital video analysis and retrieval is not as simple as analysis and retrieval of information in normal data system. The visual information of video data lies in very complex nature with its high chromatic depth and density. The extraction of visual features from noisy and complex video data has a hierarchy of different sub systems from video file to chromatic attributes. This paper introduces a novel approach to reduce the video visual feature analyzing complexity and the higher level colour complexity of video data. It comes with simple vector quantization mechanism, high rate performance approach for classification of digital video visual features. Further this approach has tested with various video formats to generate probabilistic coding mechanism. The results of this approach show that it can be further enhanced with video graphical knowledge to guide the visual feature clustering with trained knowledge base.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Univ Malaya, Fac Comp Sci & Informat Technol, Kuala Lumpur 50603, Malaysia
Uncontrolled Keywords: Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Interdisciplinary Applications; Telecommunications
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Mr. Faizal Hamzah
Date Deposited: 20 Dec 2011 03:33
Last Modified: 20 Dec 2011 03:33

Actions (login required)

View Item View Item