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A bionic tactile device is designed for object surface texture recognition, taking inspiration from the microstructure of human fingerprints. The sense of touch in humans is achieved through the frictional vibration and generation of electrical potential signals by subcutaneous receptors. Constructing a tactile sensing device involves generating distinct signals upon interacting with different materials. The piezoelectric film PVDF is particularly suitable as a sensitive material for sensors due to its excellent flexibility, strong mechanical strength, excellent dynamic response and cost-effectiveness. This paper presents the design of a PVDF-based fingerprint-inspired tactile sensor capable of differentiating various textures. By combining the collected signals with machine learning algorithms, diverse textures can be effectively identified. To demonstrate the sensor's superior performance, two experiments were conducted—one focused on recognizing different material textures, and the other on recognizing Braille characters. The accuracy achieved in these experiments was 97.4% and 96.5%, respectively, highlighting the technology's significant potential in intelligent robotics and human-computer interaction. [Display omitted] • A bionic tactile sensor with three different layers were proposed. • Two types of texture datasets were representatively constructed for analytical study. • Some eigenvalue parameters combined with machine learning algorithms was used to achieve high recognition accuracy. [ABSTRACT FROM AUTHOR]