A Minimum Spanning Tree-Based Method for Initializing the K-Means Clustering Algorithm

The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Face Localization Using Illumination-dependent Face Model for Visual Speech Recognition

A robust still image face localization algorithm capable of operating in an unconstrained visual environment is proposed. First, construction of a robust skin classifier within a shifted HSV color space is described. Then various filtering operations are performed to better isolate face candidates and mitigate the effect of substantial non-skin regions. Finally, a novel Bhattacharyya-based face detection algorithm is used to compare candidate regions of interest with a unique illumination-dependent face model probability distribution function approximation. Experimental results show a 90% face detection success rate despite the demands of the visually noisy environment.

Transmission Performance of Millimeter Wave Multiband OFDM UWB Wireless Signal over Fiber System

Performance of millimeter-wave (mm-wave) multiband orthogonal frequency division multiplexing (MB-OFDM) ultrawideband (UWB) signal generation using frequency quadrupling technique and transmission over fiber is experimentally investigated. The frequency quadrupling is achived by using only one Mach- Zehnder modulator (MZM) that is biased at maximum transmission (MATB) point. At the output, a frequency quadrupling signal is obtained then sent to a second MZM. This MZM is used for MBOFDM UWB signal modulation. In this work, we demonstrate 30- GHz mm-wave wireless that carries three-bands OFDM UWB signals, and error vector magnitude (EVM) is used to analyze the transmission quality. It is found that our proposed technique leads to an improvement of 3.5 dB in EVM at 40% of local oscillator (LO) modulation with comparison to the technique using two cascaded MZMs biased at minimum transmission (MITB) point.