One of the traditional techniques for extracting depth information is to find the disparities of corresponding points in stereo images following a biological model of three-dimensional vision. A normal binocular stereo system uses two images to determine which point in one image corresponds to a given point in the other, i.e., to find the correspondence between two images. If the distance between two cameras, i.e. the baseline, is small, no detail matching can be made. Conversely, for a large baseline, some points visible in one image will not be seen in the other thus making it difficult and sometimes even impossible to find the corresponding points. A sequence of a number of images can solve such problems in the stereo vision system. The algorithm developed here chooses the center image of a sequence of images as the reference and finds the corresponding points of its left and right halves from the images taken from its left and right, respectively. A recently developed two-dimensional power cepstrum technique to detect the translational difference between the extracted features of sequential and complex images has been proven to be very accurate and noise tolerant. The two-dimensional power cepstrum technique can be applied to any two images to determine the translational difference, i.e. disparity, between them. The resolution of the disparity depends on the baseline used. High resolution in disparity is achieved by increasing the baseline and decreasing the window size. This technique matches the corresponding points in two images with several intermediate images to reduce the error in matching from widely different perspectives. Therefore the depth information extracted from a sequence of images by the cepstrum technique is more accurate than the existing matching techniques for the stereo vision model.