An Adaptive Grid-Point Detection Method in a Pseudo-Random Structured Light Pattern

Abstract

In this paper, an adaptive grid-point detection method is developed in a pseudo-random color pattern. In the proposed method, weighted cross mask convolution and non-maximal suppression are carried out to the pattern to obtain several grid-point candidates. In order to accurately measure the point symmetry of the candidates, Harris corner detector is used to adaptively select the suitable window size. Finally, the grid-points are recognized by comparing the symmetry characteristic with a given threshold. Some experiments have been conducted to demonstrate the effectiveness of the proposed method.