A key technique for protein analysis is the geometric alignment of two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), i.e., 2-D PAGE image registration. In this study, the adaptability in elastic image registration was emphasized. According to the characteristics of 2-D gel image registration, a fuzzy-inference-rule based flexible model (FIM-FM) is proposed to model the complex transformation between 2-D gel image pairs. By introducing the concept of motion estimation, the parameter learning rules of the proposed model are derived for registration. The experiments show that the proposed algorithm is highly effective for registration of 2-D gel images and is competitive to the existing state-of-the-art algorithms.
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