基于环绕数约束模型的轮廓识别算法研究

为了解决当前图像轮廓识别算法中由于区域标记和轮廓标记性质不同,导致难以将多标记融合识别技术应用于图像轮廓识别中的问题,本文提出了一种基于环绕数约束的能量最小化模型,用以精确识别目标轮廓.在这种模型中,区域标记(如颜色和纹理均匀性)和轮廓标记(如局部对比度和连续性)通过一个目标函数进行描述,实现多标记融合识别.首先,将环绕数作为约束,将其引入到能量最小化模型中,得到区域标记与轮廓标记的线性约束;然后,对区域标记、轮廓标记以及曲率标记进行融合,实现对图像中目标轮廓的识别;最后,将能量最小化模型与标记相结合,通过比率能量函数对算法进行实例应用分析,验证算法的有效性.实验结果表明:与传统轮廓识别算法相比,所提算法具有更高的轮廓识别精度.

On Contour Recognition Algorithm Based on Winding Number Constraint Model

In order to solve the current image contour recognition algorithm,it is difficult to realize the multi-label fusion recognition because of the difference of the contour cues and the region cues,and the recognition effect is not good.In this paper,an energy minimization model has been proposed on the basis of wrapping number constraint,which can be used to accurately identify the target contour.In this model,the regional markers (such as color and texture uniformity) and contour markers (such as local contrast and continuity) are described by an objective function to implement multi-label fusion recognition.Firstly,the winding number is introduced as a constraint into energy minimization framework,and the linear constraints of the region cues and the contour cues are obtained.Secondly,the contour recognition of the target image is carried out by integrating the region cues with the contour cues and the curvature cues.And lastly,the energy minimization framework is combined with the cues and instantiated by the energy ratio function,verify the validity of the algorithm. The experimental results show that the contour recognition algorithm based on the winding number constraints model proposed in this paper is applied to the fusion of the region cues and the contour cues,and the ideal image processing effect can be obtained.