In this paper, we present a new method of detecting visual objects in digital images and video. The novelty of the proposed method is that it differentiates objects from non-objects using image edge characteristics. Our approach is based on a fast object detection method recently developed by Viola and Jones. While Viola and Jones use Harr-like features, we propose a new image feature called edge density that can be computed more efficiently. When applied to the problem of detecting people and pedestrians in images, the new feature shows very good discriminative capability compared to Harr-like features.