Large amount of multi-media content, generated by various image capturing devices, is
shared and downloaded by millions of users across the globe, every second. High …

Feature integration theory can be regarded as a perception theory, but the extraction of
visual features using such a theory within the CBIR framework is a challenging problem. To …

One of the major challenges in content-based image retrieval (CBIR) is understanding the
actual semantic meaning of images. Generally, natural images possess a rich collection of …

In this study, a new content based image retrieval (CBIR) method, which uses HSV
histogram data is proposed. The model uses the HSV histogram to find the background from …

Clinical diagnosis now plays a bigger part in today's healthcare system. Since brain cancer
is the deadliest disease in the world, it is a significant concern in the field of medical …

Abstract In Content-based Image Retrieval (CBIR), the user provides the query image in
which only a selective portion of the image carries the foremost vital information known as …

Content based image retrieval (CBIR) systems compare a query image with images in a
dataset to find similar images to a query image. In this paper a novel and efficient CBIR …

The objective of the content-based image retrieval (CBIR) system is to retrieve the visually
identical images from the database efficiently and effectively. It is a broad research realm …

Recently, DNA encoding has shown its potential to store the vital information of the image in
the form of nucleotides, namely, and, with the entire sequence following run-length and GC …

In this paper, we address the problem of multiple features fusion in instance-level image
retrieval. Achieving tremendous success in recent retrieval task, convolutional neural …