Locally Adaptive Thresholding for Single-Shot Structured Light Patterns

Abstract

Image thresholding is a challenging task due to its sensitivity to environmental variations and degradation in the quality of the captured image. Although many image thresholding methods have been introduced, most of them require the fine tuning of a thresholding parameter that is not suitable for single-shot structured light (SSSL) based projector-camera applications. In this paper, we introduce a locally adaptive thresholding method with automatic parameter selection based on the local statistics of the distinct image partitions. For assessing the proposed scheme, we introduce an evaluation that relies on mapping SSSL patterns between the camera and projector spaces. Experimental results demonstrate the effectiveness of the proposed technique by maintaining the thresholding accuracy of the baseline method, without the need to fine tune the obtained thresholding parameter or any noticeable change in the qualitative results.