摘要
重叠区域图像分离是图像处理技术中的一个重要环节,在医疗诊断、工业加工和军事防御等众多领域占据重要地位。针对当前方法在对重叠区域图像进行分离时,过于依赖极限腐蚀运算,一旦极限腐蚀运算没有较好的将图像重叠区域腐蚀开,无法得到准确的距离标记,将会导致重叠区域图像无法有效分离。提出一种基于凹点搜寻的重叠区域图像自动分离方法,在低尺度空间上,对重叠区域图像轮廓曲率进行计算;利用高斯函数的宽度参量控制重叠区域轮廓的平滑程度;计算获得重叠区域每个边缘像素的曲率后,去除曲率大于0的凸点,选取曲率极小值的点作为候选凹点,同时去除虚假凹点,完成重叠区域图像的凹点检测;根据重叠区域图像凹点个数与目标对象个数之间的对应关系确定重叠类型,给出了重叠区域图像的不同凹点匹配规则;通过连接的匹配凹点,实现重叠区域图像的自动分离。仿真测试结果证明,所提方法能够实现图像不同重叠类型的有效分离,分离对象具有较高的信噪比,结构相似性和品质,且没有发生较大形变。
This paper proposes an automatic image separation method in overlapping area based on concave spot search. In low-scale space,the contour curvature of image in overlapping area is calculated. The width parameter of Gaussian function is used to control the smoothness of contour in overlapping area. After calculating each curvature of edge pixel in overlapping area,we remove the salient point whose curvature is greater than 0,and select the point with the minimum curvature as the candidate concave point. At the same time,the false concave point is removed to complete the detection of false concave point in the overlapping area. According to the corresponding relation between number of concave points of image in overlapping area and the number of the target objects,the overlapping type is determined and the matching rule of different concave points of image in overlapping area is given. Thus,the automatic separation of overlapping images is realized through connected matching concave points. Simulation results prove that the proposed method can effectively separate different overlapping types in images. The separated objects have high signal-to-noise ratio,structural similarity and quality.
引文
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