This paper is published in Volume-7, Issue-3, 2021
Area
Information Technolgy Engineering
Author
Hari Krishnan M., Jayaraman N., Mahendran P., Dr. N. Kanya
Org/Univ
Dr. M. G. R. Educational and Research Institute, Chennai, Tamil Nadu, India
Pub. Date
25 June, 2021
Paper ID
V7I3-2117
Publisher
Keywords
SSIM - Structural Similarity Metric, VIF - Visual Information Fidelity, HVS - Human Visual System, NSS - Natural Scene Statistics, CBRD - Cross Batch Redundancy Detection, MSE - Mean-Squared Error, FSRISA - Feature-Based Sparse Representation For Image Similarity Assessment, PSNR - Peak signal-to-Matching Ratio, GUI - graphical user interface, CBIR - Content-Based Image Retrieval, IDE - Integrated Development Environment

Citationsacebook

IEEE
Hari Krishnan M., Jayaraman N., Mahendran P., Dr. N. Kanya. High-speed download cost-effective version control compression on cloud, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Hari Krishnan M., Jayaraman N., Mahendran P., Dr. N. Kanya (2021). High-speed download cost-effective version control compression on cloud. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.

MLA
Hari Krishnan M., Jayaraman N., Mahendran P., Dr. N. Kanya. "High-speed download cost-effective version control compression on cloud." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.

Abstract

Traditional techniques for image retrieval are not supported for the ever-expansive image database. These downsides can be removed by utilizing contents of the image for image retrieval. This sort of image retrieval can be accomplished with the help of cross batch redundancy detection (CBRD). When the cross batch redundancy detection (CBRD) is combinedly work with Bandwidth Energy Efficient sharing (BEES) has very precise result other than any commonly known feature detector or traditional method that are usually utilized in vision programming. In this paper we mainly focus in texture, colour ,shape and resolution of an image matching with superior accuracy and we also review some of the futuristic tool developed on CBRD