Palmprint is a novel biometric method to identify a person. Generally, there are two types of features in palmprint, i.e. structural features and statistical features. Structural features, such as lines, can characterize a palm exactly, but are difficult to be extracted and represented. Contrarily, statistical features can be extracted and represented easily, but are unable to reflect the structural information of a palmprint. The fact that the principal features of both Chinese character and palmprint are lines motivates us to try some methods of Chinese character recognition to identify palmprint. In this paper, we use the idea of an efficient Chinese character recognition method, directional element feature (DEF), to define a novel palm-print feature, named fuzzy directional element energy feature (FDEEF) which is a statistical feature containing some line structural information about palmprints. It can be extracted and represented easily and, at the same time, has a strong ability to distinguish palms. Two other low-dimensional features: global fuzzy directional element energy feature (GFDEEF) and block edge energy feature (BEEF) are also derived from FDEEF in this paper. The experimental results demonstrate the power of this method.