为降低噪音影响、改善汽车车身反光造成虚假轮廓的现象,提出了一种视觉神经元双拮抗机制和 自适应双阈值相结合的轮廓提取算法。双拮抗机制算法依据视觉神经元双拮抗原理处理图像得到亮度特 征的轮廓,用扩展的大津法(Otsu)根据轮廓亮度分布自动选取高低阈值,对初步提取的轮廓进行双阈值 处理,得到最终的汽车轮廓。利用客观性能指标对实验结果进行评价,结果表明提出的算法提升了汽车 轮廓的完整性。与经典的轮廓提取算法相比,其计算复杂度低,对图像背景的适应性较强。

In order to reduce noise influence and improve false contour phenomenon caused by automobile body reflection, a new contour extraction algorithm combining visual neurons dual antagonism mechanism and adaptive dual threshold is proposed. Original images are processed by dual antagonism mechanism algorithm to get contours of brightness characteristics according to visual neurons dual antagonism principle. High and low threshold values are selected automatically according to brightness distribution of the contours by using extended Otsu algorithm. Double threshold processing is carried out to the contour preliminary extracted, and the final automobile contour is obtained. The objective performance index is used to evaluate the experimental results. Results show that the proposed algorithm improves the integrity of automobile contour. Compared with the classic contour extraction algorithm, it has low computing complexity and good adaptability of image background.