Abstract
Most of three-dimensional (3D) content generation programs cannot generate a stereoscopic image directly. 3D content is realized by capturing the two-dimensional images of the object at different angles firstly then reconstructing the stereoscopic image by the software. The performance of a stereoscopic image will suffer if the software converting 2D to 3D image is not efficient and accurate. Square tube mirror image system is a special three-dimensional content generation designed to generate a special two-dimensional image composed of nine views (as if taken from nine different cameras), called STM image. The key information to reconstruct 3D image like depth can be extracted from these nine views after accurately segmented from the STM image. In this thesis, we present a method to analyze the STM image by recognizing the boundaries of those nine views. In the process, we simplify the problem by converting to grey scales, confine the edge detection within a certain region of the vertical and horizontal directions by taking x and y gradients of the image, utilize line segment filters to extract the boundaries of STM image, and identify those boundaries by linearly fitting the filtered image. The boundaries are defined, finally, by the four edge points and ready to be segmented. The boundary-recognition results are demonstrated by 12 STM images under different backgrounds. The average detection error after systematic correction is satisfactory.