In this paper, we present a new method for 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 developed by Viola and Jones. While Viola and Jones use Harr-like features, we propose a new image feature - the edge density - that can be computed more efficiently. When applied to the problem of detecting people and pedestrians in images, the new feature shows a very good discriminative capability compared to the Harr-like features.