基于开关式周围抑制的轮廓检测方法

传统的基于梯度的边缘检测算子旨在提取图像中所有由灰度变化引起的边缘,并不区分目标轮廓边缘和由杂波造成的干扰边缘。为提高这类算子在自然图像中检测主要轮廓边缘的性能,提出了基于开关式周围抑制的轮廓检测算法。与其他基于周围抑制的方法相比,该方法仅对干扰边缘进行抑制,对轮廓边缘不进行抑制,从而进一步提高了传统边缘算子的轮廓检测性能。利用自然图像和标准的参考轮廓边缘图像对该方法进行性能评估,结果表明,本文方法的轮廓检测性能优于传统的边缘算子及其他基于周围抑制的方法。

Contour detection based on switching surround suppression

The standard gradient-based edge detectors react to all luminance changes,irrespective of whether they are due to the contours of the objects represented in a scene or due natural textures like grass,foliage,water,and so forth.To improve their performance in detection of object contours and region boundaries in natural scenes,an algorithm called switching surround suppression was proposed which can be easily incorporated into them.Different from previous methods that deploy surround suppression,our method only exerts suppression on texture edges while leaving contours unaffected,which further improves the contour detection performance of standard gradient-based edge detectors.The proposed method was evaluated by the natural images and the standard reference contour edge images.The results showed that the proposed method is better than the standard gradient-based edge detectors as well as other methods that deploy surround suppression.