In order to correctly select the optimal threshold for image segmentation,a novel method of image segmentation based on data field is proposed.The method maps the image from grayscale space to the appropriate potential space in data field,and measures the interactions of the elements in the two-dimension histogram by taking the frequency of two-dimension gray histogram as the mass of data field,thus generating a three-dimension data field.Then,by employing the potential center elimination and combination,the optimal threshold is determined and good segmentation result is obtained without significantly increasing the time complexity.It is indicated by the experiments for standard image datasets and some noisy images that,as an alternative to OTSU,the proposed me-thod is reasonable and effective with certain noise resistance.