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ScanLag: High-throughput Quantification of Colony Growth and Lag Time
Published on: July 15, 2014
The enhanced LBG algorithm
1Institute of Computer Science and Telecommunications, Faculty of Engineering, University of Catania, Italy.
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.
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