Abstract

In order to reduce the uncertainties associated with manual selection of regions of interest (ROIs) commonly used in Surface Plasmon Resonance (SPR) imaging system, we proposed and implemented an automatic image segmentation method in an embedded system to facilitate the potential real-time applications. Intuitive marker-controlled watershed algorithm is developed to segment ROIs (reaction, blank, and background regions) from images acquired from an experimental image SPR system. The marker assignment algorithms and pre-processing algorithms are executed in parallel by multi-threading programming on the multi-core embedded system to both real-time and good quality of segmentation. This method exhibited a good robustness in a series of ROIs segmentation test. Furthermore, the intensity response from triplicate detection of glucose standard solutions indicated a good reproducibility of data. The linear range was from 2.5 mg/mL to 20.4 mg/mL, with a correlation coefficient (R2) of 0.999 and sensitivity of 2.69 a.u./mg/mL. In conclusion, the proposed automatic image segmentation method effectively makes the measurement more precise and simplified.

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