Image Capturing and Deleting Duplicate Images through Feature Extraction using Hashing Techniques

Image Capturing and Deleting Duplicate Images through Feature Extraction using Hashing Techniques
  IJETT-book-cover           
  
© 2024 by IJETT Journal
Volume-72 Issue-1
Year of Publication : 2024
Author : Prathima Ch, R. Swathi, K. Suneetha, I. Suneetha, B. V. Suresh Reddy, Siva Kumar Depuru
DOI : 10.14445/22315381/IJETT-V72I1P107

How to Cite?

Prathima Ch, R. Swathi, K. Suneetha, I. Suneetha, B. V. Suresh Reddy, Siva Kumar Depuru, "Image Capturing and Deleting Duplicate Images through Feature Extraction using Hashing Techniques," International Journal of Engineering Trends and Technology, vol. 72, no. 1, pp. 64-70, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I1P107

Abstract
Nowadays, a major issue in society is the duplication of all the objects in terms of images while capturing. For example, if a folder is on the PC, it allows the storage of the same image with different names. Here, the waste of memory is more. So, to avoid duplication of images, needed to scan the content inside the file and identify whether the images are duplicates or not. This process is known as CBIR (Content Based Image Retrieval). There are many techniques to find duplicate images. CNN (Convolution Neural Networks), Phash (perceptual hash), Block Truncation Technique etc., are used to find the image similarity identification and to avoid wastage of memory. The proposed work is to capture images and store them in a folder to identify duplicate images and delete them. Developed a user interface to delete duplicate images using a folder path for user-friendly usage. There are various techniques for image deduplication and all the techniques will not work effectively. There is a need for image deduplication in a wide range of domains like income tax, banks, and many other private organizations and private corporations where there store many images that are duplicates. Even some of the social media companies store images that are shared using the app. All these need to be deduplicated to save money, maintenance costs and storage space.

Keywords
Images, Convolutional Neural Network, Deep Learning, Deduplication.

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