Edge chain detection by applying Helmholtz principle on gradient magnitude map
Xiaohu Lu, Jian Yao, Li Li, Yahui Liu, Wei Zhang · 2016
In this paper, we present an efficient edge chain detection algorithm by applying the Helmholtz principle on the gradient magnitude map of an image. An edge chain validation method is proposed which uses the “relative number of false alarms” (RNFA) instead of the traditional “number of false alarms” (NFA). The edge chains are detected first and then validated according to their RNFA values. In this way, edge chains that are weak in gradients but meaningful in vision can be detected. To evaluate the proposed edge chain detector in quantity, an edge chain detection benchmark which consists of 25 labeled images in different scenes was built. The proposed edge chain detector was tested in this benchmark, and the experimental results sufficiently demonstrate that the proposed edge chain detector outperforms the state-of-the-art methods.