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THE ENHANCED LBG ALGORITHM USING NERAL NETWORKS

Platform : DSP

AIM: Implementation of LBG Algorithm by using neural networks ABSTRACT Clustering applications cover several fields such as audio and video data compression, pattern recognition, computer vision, medical image recognition, etc. In this paper, we present a new clustering algorithm called Enhanced LBG (ELBG). It belongs to the hard and K-means vector quantization groups and derives directly from the simpler LBG. The basic idea we have developed is the concept of utility of a codeword, a powerful instrument to overcome one of the main drawbacks of clustering algorithms: generally, the results achieved are not good in the case of a bad choice of the initial codebook. We will present our experimental results showing the ELBG is able to find better codebooks than previous clustering techniques and the computational complexity is virtually the same as the simpler LBG. LEARNING OBJECTIVE: Use of LBG algorithm for the image compression INPUT: Raw Image OUTPUT : Compressed version of the Image APPLICATIONS: To save the transmission time and to enhance data rate over the network. SOFTWARE TOOL USED: MATLAB 2007A

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