This paper proposes an object oriented face region detection and tracking method using range color information. Range segmentation of the objects are obtained from the complicated background using disparity histogram (DH). The facial regions among the range segmented objects are detected using skin-color transform technique that provides a facial region enhanced gray-level image. Computationally efficient matching pixel count (MPC) disparity measure is introduced to enhance the matching accuracy by removing the effect of the unexpected noise in the boundary region. Redundancy operations inherent in the area-based matching operation are removed to enhance the processing speed. For the skin-color transformation, the generalized facial color distribution (GFCD) is modeled by 2D Gaussian function in a normalized color space. Disparity difference histogram (DDH) concept from two consecutive frames is introduced to estimate the range information effectively. Detailed geometrical analysis provides exact variation of range information of moving object. The experimental results show that the proposed algorithm works well in various environments, at a rate of 1 frame per second with 512 480 resolution in general purpose workstation.

A new design and experimental results of a microstrip-fed ultra-wideband Fermi antenna at millimeter-wave frequencies are presented. By utilizing a new microstrip-to-CPS balun (or transition), which provides wider bandwidth than conventional planar balun, the design of microstrip-fed Fermi antenna is greatly simplified. The proposed Fermi antenna demonstrates ultra-wideband performance for the frequency range of 23 to over 58 GHz with the antenna gain of 12 to 14 dBi and low sidelobe levels. This design yields highly effective solutions to various millimeter-wave phased-arrays and imaging systems.