<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Due to the availability of a large number of image editing software, it is very easy to find duplicate copies of original images. In such a situation, there is a need to develop a robust technique that can be used for the identification of duplicate copies apart from differentiating it from different images. In this paper, we have proposed an image hashing technique based on uniform Local Binary Pattern (LBP). Here, the input image is initially pre-processed before calculating the Local Binary Pattern (LBP) which is used for image identification. Experiments show that proposed hashing gives excellent performance against the Histogram equalization attack. The Receiver Operating Curve (ROC) indicates that the proposed hashing also performs better in terms of robustness and discrimination. Support Vector Machine (SVM) classifier shows that generated features can easily classify images into a set of similar and different images, and can classify new data with a high level of accuracy.</p></abstract>

Due to the availability of a large number of image editing software, it is very easy to find duplicate copies of original images. In such a situation, there is a need to develop a robust technique that can be used for the identification of duplicate copies apart from differentiating it from different images. In this paper, we have proposed an image hashing technique based on uniform Local Binary Pattern (LBP). Here, the input image is initially pre-processed before calculating the Local Binary Pattern (LBP) which is used for image identification. Experiments show that proposed hashing gives excellent performance against the Histogram equalization attack. The Receiver Operating Curve (ROC) indicates that the proposed hashing also performs better in terms of robustness and discrimination. Support Vector Machine (SVM) classifier shows that generated features can easily classify images into a set of similar and different images, and can classify new data with a high level of accuracy.

Image Copy Detection Based on Local Binary Pattern and SVM Classifier

Department of Computer Engineering & Applications

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Image Copy Detection Based on Local Binary Pattern and SVM Classifier"}

Due to the availability of a large number of image editing software, it is very easy to find duplicate copies of original images. In such a situation, there is...

Image Copy Detection Based on Local Binary Pattern and SVM Classifier

Data publikacji: 12 cze 2020

Zakres stron: 59 - 69

Otrzymano: 12 gru 2019

Przyjęty: 03 kwi 2020

DOI: https://doi.org/10.2478/cait-2020-0016

Słowa kluczowe
Content-based copy Detection, Digital watermarking, Local Binary Pattern, Support Vector Machine, Image forensics, Image hashing

© 2020 Mayank Srivastava et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Image Copy Detection Based on Local Binary Pattern and SVM Classifier

Data publikacji: 12 cze 2020

Zakres stron: 59 - 69

Otrzymano: 12 gru 2019

Przyjęty: 03 kwi 2020

DOI: https://doi.org/10.2478/cait-2020-0016

Słowa kluczoweContent-based copy Detection, Digital watermarking, Local Binary Pattern, Support Vector Machine, Image forensics, Image hashing

© 2020 Mayank Srivastava et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
Content-based copy Detection, Digital watermarking, Local Binary Pattern, Support Vector Machine, Image forensics, Image hashing