We present an approach to detect eyes in color images. First of all, RGB facial image is converted to YCbCr one. According to YCbCr facial image, the proposed algorithm constructs two EyeMaps, one map from luminance component (EyeMapL) and the other from chrominance components (EyeMapC). When the two separate EyeMaps are constructed, we combine them to make final EyeMap. We use final EyeMap to generate potential eye candidates and then perform an extra phase on these candidates to determine suitable eye pair. This extra phase consists of flexible thresholding and geometrical tests. We test our approach on CVL and Iranian databases. Simulation results showed this phase improved the correct detection rate by about 12% and reach 98% success rate on the average