计算机与现代化

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一种改进的Canny图像分割算法

  

  1. (四川大学制造科学与工程学院,四川成都610065)
  • 收稿日期:2018-01-30 出版日期:2018-09-11 发布日期:2018-09-11
  • 作者简介:杨少令(1990-),男,河南安阳人,四川大学制造科学与工程学院硕士研究生,研究方向:机器视觉,结构设计; 刁燕(1970-),女,四川西昌人,副教授,硕士生导师,硕士,研究方向:结构设计,机器视觉; 罗华(1971-),男,四川成都人,讲师,博士,研究方向:机器人; 徐天雄(1993-),男,北京人,硕士研究生,研究方向:机器视觉,机器人控制。

An Improved Canny Image Segmentation Algorithm

  1. (School of Manufacturing Science and Engineering, Sichuan University, Chengdu 610065, China)
  • Received:2018-01-30 Online:2018-09-11 Published:2018-09-11

摘要: 针对目前图像分割算法普遍存在噪音鲁棒性差、易发生细小边界信息缺失以及适用范围较窄的缺点,改进Canny边缘提取算法中的问题阈值并与原色特征提取加权融合。首先针对Canny算子阈值的自适应性问题,通过计算图像背景与目标之间的类方差来减少错分概率来决定阈值。然后,在具有丰富信息的彩色图像上提出R、G、B这3种原色特征,通过原色特征提取的分割图像与阈值分割提取的图像加权融合形成全新的分割图像。该算法不仅克服了传统分割提取算法边缘信息丢失、鲁棒性差的问题,而且提高了细节点的单位精度,实验结果表明了本文改进Canny边缘算法的有效性。

关键词: 自适应性, 原色特征, 图像融合

Abstract: Aiming at the shortcomings of image segmentation algorithm, such as poor noise robustness, small boundary information easily loss and narrow application scopes, we improve the threshold value of Canny edge extraction algorithm and extract weighted fusion with chromatic feature. According to the adaptive problem of the Canny operator threshold, the threshold is determined by calculating the class variance between the image background and the target to reduce the error probability. Then, we propose three color features of R, G and B on colorful images with rich information. The new segmentation images are fused by thresholding and segmented images extracted by chromaticity feature extraction. The algorithm not only overcomes the problem of edge information loss and poor robustness of the traditional segmentation and extraction algorithm, but also improves the unit accuracy of the detail. The experimental results show the effectiveness of the improved Canny edge algorithm.

Key words: adaptability, chroma features, image fusion

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