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Along with the miniaturization and ease-to-use of biomedical instruments,the increasing demand of health monitoring at anywhere and anytime elevates the need for developing the point of care testing(POCT).Photonic crystal microbeads(PCBs)as one kind of good encoded microcarriers can be integrated with microfluidic chips in order to realize cost-effective and high sensitive multiplex bioassays.However,there are difficulties in analyzing them by imaging towards automation assays due to the characters of the PCBs and the unique detection manner.In this paper,we report a novel image processing and analyzing method for the microfluidic chip based on PCBs.Adaptive enhancement and statistical pattern recognition algorithm are utilized for the automatic extraction of photonic crystal microbeads in the images.Subsequently,we propose a decoding algorithm to extract the characteristic colors from the iridescent microbeads and use a gating strategy to identify the different color codes.Our experiments show that the automatic extraction algorithm has better applicability and higher robustness in comparison with other existing biochip image processing methods.And the decoding algorithm performs well for various microbeads with accuracy approaching 90%.