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With the development of data generation, photographs are being created and stored daily on a remarkable scale. Analyses of huge picture collections play important roles in an expansion of packages, starting from private album control, remedy, protection, to remote sensing. However, the technologies and gear that empower customers to discover and make sense of large image collections are lagging. The latest years have witnessed a growing hobby in using visualization strategies, which include treemaps, node-hyperlink diagram], and scatterplots, for exploring big photograph collections. Those strategies can offer users with a precis of photograph collections with the aid of grouping photos primarily based on picture similarities, which can be obtained in step with intrinsic functions (i.e., image pixels and metadata) or consumer -generated tags. Users are similarly allowed to drill down to man or woman photos interactively. Visualization methods ha ve been correctly applied in different systems, such as PhotoMesa, photoland, and Image Hive, yet the processes largely ignore the semantic contents and relationships of gadgets embedded in the images. Here we surv the different papers that uses different methods for the image processing.

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How to Cite
Abirami B, & Sankar K. (2021). A survey on image processing. International Journal of Intellectual Advancements and Research in Engineering Computations, 8(1), 26–30. Retrieved from