doi:10.16186/j.cnki.1673-9787.2019100045

Received:2019/10/17

Revised:2020/01/13

Published:2021/01/15

A tensor voting algorithm for image line feature extraction based onimproved voting field

WANG Li1, SU Lijun2

1.Yinxing Hospitality Management College,Chengdu Uinversity of Information Technology,Chengdu 611730 ,Sichuan,China;2.School of Science,Xi' an University of Technology，Xi' an,710054 ，Shaanxi,China

Abstract:Tensor voting algorithm is calculated by the principle of human perception function,which has strong robustness,non-iteration,uniqueness of parameters and other characteristics. Its non-iteration has the significance feature of saving computation time,so,it is widely used in image line feature extraction. However,in some complex noisy images,it cannot obtain more continuous saliency line feature information. In order to solve this problem,an improved iterative tensor voting algorithm was proposed,which mainly improved the voting domains iteratively,so that the improved tensor voting algorithm could extract more continuous salient line features. Compared with the traditional tensor voting algorithm,the proposed method in this paper not only shortened the calculation time,but also extracted more continuous line feature images.

Key words:tensor voting algorithm;voting domain;iteration;image line feature

 一种面向图像线特征提取的改进投票域的张量投票算法_王莉.pdf