This paper presents the significance of glottal activity and glottal signature for capturing speaker characteristics via text-dependent speaker verification (SV) system. Dynamic Time Warping (DTW) based SV system is used as base line system for matching, where detection of end-points is based on the Glottal Activity (GA) region obtained through the zero frequency filter signal (ZFFS). The GA regions are detected by exploiting the strength of excitation and periodic nature of speech and glottal signal. Identified GA regions are further processed to consider packed GA regions after removing the silence regions in between detected GA region for template matching. Using periodic nature of glottal signal in the GA region, each cycle is divided into four quadrants by considering peak and zero crossings to produce the glottal signatures and used as excitation source features. The performance of proposed end point detection method is tested by conducting text dependent SV experiments and it is compared with energy based end point detection method. The system performance improves further when feature selection is done through ZFFS algorithm in a packed GA region over the energy based Voice Activity Detection(VAD) approach. © 2014 IEEE.