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X-ray diffraction is a common technique for determining crystal structures. The average time needed for the solution of a protein structure has been drastically reduced by a number of recent experimental and theoretical developments. Since high-throughput protein crystallography benefits from full automation of all steps that are carried out on a synchrotron beamline, an automatic crystal centring procedure is important for crystallographic beamlines. Fully automatic crystal alignment involves the application of optical methods to identify the crystal and move it onto the rotation axis and into the X-ray beam. Crystal recognition has complex dependencies on the illumination, crystal size and viewing angles due to effects such as local shading, inter-reflections and the presence of antifreezing elements. Here, a rapid procedure for crystal centring with multiple cameras using region segment thresholding is reported. Firstly, a simple illumination-invariant loop recognition and classification model is used by slicing a low-magnification loop image into small region segments, then classifying the loop into different types and aligning it to the beam position using feature vectors of the region segments. Secondly, an edge detection algorithm is used to find the crystal sample in a high-magnification image using region segment thresholding. Results show that this crystal centring method is extremely successful under fluctuating light states as well as for poorly frozen and opaque samples. Moreover, this crystal centring procedure is successfully integrated into the enhanced Blu-Ice data collection system at beamline BL17U1 at the Shanghai Synchrotron Radiation Facility as a routine method for an automatic crystal screening procedure.
