This paper presents the establishing of a biconvex fuzzy variational (BFV) method with teaching learning based optimization\n(TLBO) for geometric image segmentation (GIS). Firstly, a biconvex object function is adopted to process GIS. Then, TLBO is\nintroduced to maximally optimize the length penalty item (LPI), which will be changed under teaching and learner phase of TLBO,\nmaking the LPI closer to the target boundary. Afterward, the LPI can be adjusted based on fitness function, namely, the evaluation\nstandards of image quality. Finally, the LP is combined item with the numerical order to get better results. Different GIS strategies\nare compared with various fitness functions in terms of accuracy. Simulations show that the presented method is more effective in\nthis area.
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