In this paper we present a new monochromatic pattern for a robust structured light coding based on the spatial neighborhood scheme using the M-array approach. The proposed pattern is robust as it allows a high error rate characterized by an average Hamming distance higher than 6. We tackle the design problem with the definition of a small set of symbols associated to simple geometrical primitives. One of these primitives embeds the local orientation of the pattern. This is helpful while performing the search for the relevant neighborhood during the decoding process. The aim of this work is to use this pattern for the real-time 3-D reconstruction of dynamic scenes, particularly in endoscopic surgery, with fast and reliable detection and decoding stages. Ongoing results are presented to assess both the capabilities of the proposed pattern and the reliable decoding algorithm with projections onto simple 3-D scenes and onto internal structures of a pig abdomen.

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Structured light based patterns provide a means to capture the state of an object shape. However it may be inefficient when the object is freely moving, when its surface contains high curvature parts or in out of depth of field situations. For image-based robotic guidance in unstructured and dynamic environment, only one shot is required for capturing the shape of a moving region-of-interest. Then robust patterns and real-time capabilities must be targeted. To this end, we have developed a novel technique for the generation of coded patterns directly driven by the Hamming distance. The counterpart is the big amount of codes the coding/decoding algorithms have to face with a high desired Hamming distance. We show that the mean Hamming distance is a useful criterion for driving the patterns generation process and we give a way to predict its value. Furthermore, to ensure local uniqueness of codewords with consideration of many incomplete ones, the Perfect Map theory is involved. Then, we describe a pseudorandom/exhaustive algorithm to build patterns with more than 200×200 features, in a very short time, thanks to a splitting strategy which performs the Hamming tests in the codeword space instead of the pattern array. This leads to a significant reduction of the computational complexity and it may be applied to other purposes. Finally, real-time reconstructions from single images are reported and results are compared to the best known which are outperformed in many cases.