


Volume 20 No 4 (2022)
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Fast adaptive up scaling of low structured images using a hierarchical filling strategy
ANKIT NEGI
Abstract
Due to the explosion of online and multimedia content, there is now an overwhelming quantity of information available in the form of still photographs, moving pictures, and sound recordings. As a result, there is a need for efficient and effective methods of storing and retrieving multimedia data like photos. Visual content is used to guide the search, navigation, and retrieval processes in Content Based Image Retrieval (CBIR). Images include information about the items they portray, such as their colours, textures, shapes, and locations. Colour, texture, and form are all examples of low-level qualities that can only tell you so much about an image's content. As a result, a semantic gap emerges between how pictures are understood visually and how they are represented using simple attributes. newline Using low-level traits and their combinations, researchers from all across the globe are attempting to bridge this semantic divide. We identify a number of issues with current low-level features and retrieval methods, and we offer some potential fixes. newline As the volume and diversity of photos in a Content Based Image Retrieval system's database grows, the system's accuracy tends to decline. This may lead to the retrieval of pictures that seem similar but convey distinct semantic notions. In addition, precise picture segmentation is necessary for form feature extraction. However, since segmenting images remains an open problem, extracting shape features is not very trustworthy. To address these issues, this article proposes a CBIR that employs a multistage retrieval technique. newline A picture's low-level details might be either regional or worldwide. Both global and local characteristics may be retrieved from a picture, with the former relying on the whole frame and the latter on only a small section of it. CBIR systems that rely on regional traits are known as RBIRs. In most cases, an RBIR system's accuracy exceeds that of its comparable global CBIR. There is a need for precision in question formulation and a longer response time in conventional RBIR systems.
Keywords
Region Based Image Retrieval systems (RBIR), multimedia, segmentation
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