查询结果:   刘千,葛阿雷,史伟.形态学与RCF相结合的唐卡图像边缘检测算法[J].计算机应用与软件,2019,36(6):196 - 201,242.
中文标题
形态学与RCF相结合的唐卡图像边缘检测算法
发表栏目
图像处理与应用
摘要点击数
833
英文标题
THANG KA IMAGE EDGE DETECTION ALGORITHM BASED ON MORPHOLOGY AND RCF
作 者
刘千 葛阿雷 史伟 Liu Qian Ge Alei Shi Wei
作者单位
宁夏大学信息工程学院 宁夏 银川 750021     
英文单位
School of Information Engineering, Ningxia University, Yinchuan 750021, Ningxia, China     
关键词
唐卡图像 边缘检测 CNN 形态学边缘检测 RCF网络模型
Keywords
Thang ka image Edge detection CNN Morphological edge detection RCF network model
基金项目
国家自然科学基金项目(61662060)
作者资料
刘千,硕士生,主研领域:西夏文物数字化保护,数字图像处理。葛阿雷,硕士生。史伟,教授。 。
文章摘要
唐卡图像的内容丰富,纹理信息复杂。边缘检测在唐卡图像分析研究中具有非常重要的意义,因为唐卡图像轮廓含有大量的图像数据信息。数学形态学方法提取的边缘光滑连续,但是对复杂的边缘检测时会存在模糊不清晰的现象。卷积神经网络(CNN)可以提取很多高层的、多尺度的信息。为此提出的边缘检测方法,用优化的数学形态学算法提取原图像边缘;利用训练的RCF网络模型提取原图像的边缘。根据小波变换的分解与重构原理将以上方法得出的图像边缘融合,从而得到更加完整光滑的图像边缘。实验表明,融合后的图像边缘更加清晰连续,轮廓信息更符合人类的视觉认知,去掉了无效的细节纹理,更有利于唐卡图像后续研究。
Abstract
Thang ka image is rich in content and complex in texture information. Edge detection is very important in the analysis of Thang ka image, because Thang ka image contour contains a lot of image data information. The edges extracted by mathematical morphology method are smooth and continuous, but there is ambiguity in complex edge detection. Convolutional neural network(CNN) can extract a lot of high-level and multi-scale information. The proposed edge detection method used the optimized mathematical morphology algorithm to extract the original image edge. Then, the training RCF network model was used to extract the edges of the original image. According to the decomposition and reconstruction principle of wavelet transform, we obtained the image edges by the above method to fuse, getting more complete and smooth image edges. Experiments show that the fused image edge is clearer and more continuous, the contour information is more in line with human visual cognition, and the invalid detail texture is removed. It is more conducive to the follow-up study of Thang ka image.
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