Fingerprint features recognition which can be used to distinguish between individuals is an intriguing study with many potential applications. In this paper, a new method for fingerprint recognition based on multifractal spectrum theory was proposed. The recognition process can be divided into the following main steps: (1) Extracting the core point in fingerprint; (2) Fragmenting the fingerprint image to get a subimage with fixed size; (3) Thinning the fingerprint image by using an improved

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... algorithm; (4) Segmenting the curves in fingerprint image into digital straight segments with normalized straight length threshold; (5) Selecting the appropriate dividing scale to segment the processed fingerprint image; (6) Calculating and analyzing the multifractal spectrum curve ) (  f  ; (7) Fitting curve equation and extracting the characteristic parameters of ) (  f  ; (8) Finally, the parameters matching and fingerprint feature recognition. A large number of experimental results show that our method is effective. 258 Copyright ⓒ 2015 SERSC straight segments based on multifractal spectrum theory. The multifractal spectrum of processed fingerprint was calculated by using inclination functions. An quadratic equation was extracted from the multifractal spectrum curve ) (  f  , which can represent the features of fingerprint. A large number of experimental results show that this method is feasible.