Circular object detection based on separability and uniformity of feature distributions using Bhattacharyya Coefficient

This paper proposes a robust detection method for circular objects in noisy and inhomogeneous contrast image. This method detects circular objects not by the difference in image intensities between the object interior and its surrounding, but by the separability and uniformity of the image intensity distributions as calculated by Bhattacharyya Coefficient. The proposed method can detect obscure and textured circular objects, both of which are challenges for conventional methods. In addition, this method does not incur the cost of texture learning. Experiments demonstrate the effectiveness and robustness of the proposed method.