This paper proposes a fuzzy logic based edge detector for feature extraction in biometric systems such as face and palm print recognition. Edge detection is carried out by means of global (histogram of gray levels) and local (pixels within in a window) information. The local information is fuzzified by employing a modified Gaussian membership function. Using the contrast intensification operator, the image is enhanced to the required level of visual quality by entropy optimization of fuzzification parameters. Furthermore, the local edge detection operator is applied on the enhanced image using parameters obtained from entropy optimization. Finally, a simple threshold is applied to produce the skeleton image. Results demonstrate that this edge detector is well suited for feature extraction in biometric image systems.