Abstract
Vector quantization is used as a method to compress information such as many points in a given space, into reduced representative points. Each of the representative points has the least distortion from the other points. Further, Voronoi partition technique is used to divide the space into segregated small spaces. Representative points represent the points in the segregated small spaces. This report proposes a new method for improving the vector quantization so as to make an approximately equal number of points to comprise each area. One of the applications of this vector quantization method is the evaluation of illumination environment. In this case, points represent positions where human beings (occupant: in this report, they are students) exist at a sampling time in an illuminated space. The general evaluation of illumination value is obtained from the measured values of uniformly divided points in the space. However, this proposed method is comprised of specific measured points corresponding to the positions where human beings exist. Therefore, this evaluation is a better method for the evaluation of illuminating environments for human beings rather than more traditional uniformly spaced illumination measurement methods.
