• K.Sudha Devi
• G.B.Subhiksha
• S.Vagrasri
• S.Varshini

Image retrieval is a fundamental task in computer vision and has numerous applications in various fields. This abstract presents a method for image retrieval using query image features, specifically focusing on the popular Scale-Invariant Feature Transform (SIFT) algorithm for feature extraction and distance calculation. The proposed approach begins with the extraction of SIFT features from a collection of images, creating a database of keypoints and descriptors. These features capture the distinctive characteristics of local image regions, allowing for robust matching and retrieval. Another big problem is the security of private cloud data, which includes query queries, the search tree, and outsourced photos. First, employ a feature extraction approach for integrated picture features, which consist of basic elements like colour and shape. Specifically, the suggested method can achieve logarithmic search time since it makes use of a balancing index tree. Second, the secure inner product is used to encrypt the image and query feature. Install a mechanism to identify duplicate image content as well. When a query image is provided, SIFT feature extraction is performed on the query image, generating key points and descriptors that represent its visual attributes. Subsequently, a distance calculation technique, such as Euclidean distance is employed to compare the query image features with the features of images in the database. This comparison quantifies the similarity between the query image and the images in the database. Based on the calculated distances, the retrieved images are ranked according to their similarity to the query image. Images with smaller distances are considered more similar and are presented as the top-ranked search results. The image retrieval system employing SIFT feature extraction and distance calculation offers a robust and efficient solution for finding visually similar images in large databases. It enables applications such as content-based image search, image recommendation systems, and image clustering, contributing to advancements in fields such as multimedia retrieval, visual analytics, and image understanding.

1. Blockchain technology 2. Cloud image processing 3. Similarity search algorithms 4. Distributed computing 5. Data privacy protection 6. Decentralized storage systems 7. Secure computation protocols 8. Cryptographic techniques 9. Scalable blockchain solutions 10. Performance optimization

"An Efficient Blockchain Assisted Similarity Search On Cloud Images.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.b360-b365, March-2024, Available :http://www.jetir.org/papers/JETIR2403147.pdf

"An Efficient Blockchain Assisted Similarity Search On Cloud Images.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppb360-b365, March-2024, Available at : http://www.jetir.org/papers/JETIR2403147.pdf