LAUSR

Abstract Phase-shifted depth segmentation, which is facilitated by the phase-shift invariance of the singular points in different wrapped phase maps, has the advantages of being immune to color, texture, and camera exposure. However, because the phase sensitivity is distributed unevenly, it is difficult to perform this type of depth segmentation properly in some special regions. Instead, this paper presents an omnidirectional method for depth segmentation without the need for precalibration or complementary cues. During data acquisition, two groups of orthogonal phase-shifted patterns are cast sequentially onto the target objects. A least-squares algorithm is then applied to these fringe patterns, and two sets of phase sequences are calculated separately. Using the proposed multi-scale enhancement technology, objects with abruptly changing surfaces can be segmented into different parts. Simulations show that even under a noisy environment (namely a signal-to-noise ratio of 10), the correct rate of the proposed framework still reaches 98.97%. Verification experiments show that the proposed method performs omnidirectional depth segmentation effectively, thereby offering a solution to the problem of mis-segmentation in phase-insensitive regions.