Palmprint is a new emerging biometric feature for personal recognition. Palm lines, which consist of principal lines and wrinkles, are stable and essential traits for palmprint-based individual identification and can be extracted in low-resolution images. Therefore, it is the natural and reliable way to extract palm lines for personal authentication. However, the research on palm-line detection has done little. Due to special properties of palmprint, in addition to the structure feature, width of the palm-line, which generally reflects strength information, is important to identify palms especially when various palmprints have similar structures. In this paper, a novel palm-line detector is proposed to simultaneously extract structure and strength features of palm lines by minimizing a local image area which is of similar brightness to each individual pixel. A stable and sensible similarity function for brightness comparison is used to obtain the initial line responses. In order to give smooth and isotropic responses, a Gaussian weighting mask is defined as the local image area. Further, the relation between the size of Gaussian weighting mask and the width of detected palm lines is analyzed. The presented method has been tested on the PolyU Palmprint Database. Experimental results illustrate the effectiveness of this palm-line detector.