Similarity Score of Two Images using Different Measures

被引：0

作者：

Appana, Varshini ^{[1
]}

Guttikonda, Tulasi Manasa ^{[1
]}

Shree, Divya ^{[1
]}

Bano, Shahana ^{[1
]}

Kurra, Himasri ^{[1
]}

机构：

[1] Koneru Lakshmaiah Educ Fdn, Dept Cse, Vaddeswaram, India

来源：

PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT 2021) | 2021年

关键词：

Image Processing; Similarity; Pixel Similarity; Structural Similarity; Earthmover's Distance;

D O I：

10.1109/ICICT50816.2021.9358789

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the field of computer vision and image processing, image similarity has been a central concern for decades. If you compare two pictures, Image Similarity returns a value that tells you how physically they are close. A quantitative measure of the degree of correspondence between the images concerned is given by this test. The score of the similarity between images varies from 0 to 1. In this paper, ORB (Oriented Fast Rotated Brief) algorithm is used to measure the similarity and other types of similarity measures like Structural Similarity Index (SSIM), pixel similarity, Earth mover's Distance are used to obtain the score. When two images are compared, it shows how much identical (common) objects are there in the two images. So, the accuracy or similarity score is about 87 percent when the two images are compared.

引用

页码：741 / 746

页数：6

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