AI-Based Copyright Detection Of An Image In a Video Using Degree Of Similarity And Image Hashing

TL;DR

This paper presents an AI-based method combining image hashing and neural networks to detect copyrighted images within videos by assessing their degree of similarity, addressing challenges in visual copyright infringement detection.

Contribution

It introduces a novel approach integrating image hashing and AI algorithms for more accurate detection of copyrighted images in videos, including less prominent segments.

Findings

Effective detection of copyrighted images in videos.

Improved accuracy over traditional methods.

Capability to identify partial or less visible copyrighted content.

Abstract

The expanse of information available over the internet makes it difficult to identify whether a specific work is a replica or a duplication of a protected work, especially if we talk about visual representations. Strategies are planned to identify the utilization of the copyrighted image in a report. Still, we want to resolve the issue of involving a copyrighted image in a video and a calculation that could recognize the degree of similarity of the copyrighted picture utilized in the video, even for the pieces of the video that are not featured a lot and in the end perform characterization errands on those edges. Machine learning (ML) and artificial intelligence (AI) are vital to address this problem. Numerous associations have been creating different calculations to screen the identification of copyrighted work. This work means concentrating on those calculations, recognizing designs inside the information, and fabricating a more reasonable model for copyrighted image classification and detection. We have used different algorithms like- Image Processing, Convolutional Neural Networks (CNN), Image hashing, etc. Keywords- Copyright, Artificial Intelligence(AI), Copyrighted Image, Convolutional Neural Network(CNN), Image processing, Degree of similarity, Image Hashing.