Similarity Measure Based on Distance of Dual Hesitant Fuzzy Sets and Its Application in Image Feature Comparison and Recognition

ABSTRACT

In this paper, we propose the distance-based similarity measure of dual hesitant fuzzy sets (DHFSs) and apply it to the image feature comparison and recognition. Based on distance-based similarity measure of DHFS, we establish a comprehensive assessment method of image features to compare the images, where five criteria are represented by DHFSs to assess the image features. By the proposed method, we can determine ranking order of the six alternative images. The assessment results show that the proposed method is simple and effective to solve the problem of image feature comparison and image recognition, and provides a new assessment method for computer image processing experts.

Keywords:

Image feature comparison, Image recognition, Image processing, Dual hesitant fuzzy set, Distance-based similarity measure.