摘要
针对医学领域中的红细胞图像要求测出细胞面积、圆度及个数等特征,提出一种基于分形维数的图像边缘提取方法。以分形布朗随机场模型为依据,计算每个像元的分形维数,将原来的灰度空间映射成分形维数空间,在该空间进行边缘检测。实验结果证明,在选择最佳窗口大小的情况下,该方法能突显医学细胞图像的检测特征,并且具有很强的抗噪声能力。
In medical applications, the image of red blood cells requires the ability to extract the relevant features, such as a cell area, roundness and number, etc. For extracting the features of the image, this paper presented an image edge detection method based on fractal dimension. The method is based on fractal brownian random field model. It maps gray space into fractal dimension space by calculating the fractal dimension of every pixel, and then it completes the edge de- tection in the fractal dimension space. The experimental results show that, in the case of the best window size, this method can highlight features of medical cell image,and has a strong ability to resist noise.
出处
《计算机科学》
CSCD
北大核心
2015年第6期296-298,共3页
Computer Science
基金
广东省自然科学基金(2010B050900016)
中央高校基本科研业务费专项资金(21613323)
国家自然科学基金国际合作与交流项目(21614605)资助
