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The aim of a Content-Based Image Retrieval (CBIR) system, also known as Query by Image Content (QBIC), is to help users to retrieve relevant images based on their contents. CBIR technologies provide a method to find images in large…

计算机视觉与模式识别 · 计算机科学 2020-07-10 Aman Chadha , Sushmit Mallik , Ravdeep Johar

Content-based image retrieval (CBIR) systems have emerged as crucial tools in the field of computer vision, allowing for image search based on visual content rather than relying solely on metadata. This survey paper presents a comprehensive…

计算机视觉与模式识别 · 计算机科学 2023-12-19 Hamed Qazanfari , Mohammad M. AlyanNezhadi , Zohreh Nozari Khoshdaregi

The explosive increase and ubiquitous accessibility of visual data on the Web have led to the prosperity of research activity in image search or retrieval. With the ignorance of visual content as a ranking clue, methods with text search…

多媒体 · 计算机科学 2017-09-05 Wengang Zhou , Houqiang Li , Qi Tian

The purpose of this Paper is to describe our research on different feature extraction and matching techniques in designing a Content Based Image Retrieval (CBIR) system. Due to the enormous increase in image database sizes, as well as its…

多媒体 · 计算机科学 2010-02-10 Mr. Kondekar V. H. , Mr. Kolkure V. S. , Prof. Kore S. N

The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases, a specified number of images similar in visual and semantic content to a so-called query image. To bridge the semantic…

信息检索 · 计算机科学 2015-02-12 Smarajit Bose , Amita Pal , Jhimli Mallick , Sunil Kumar , Pratyaydipta Rudra

Content-Based Image Retrieval (CBIR) systems have been widely used for a wide range of applications such as Art collections, Crime prevention and Intellectual property. In this paper, a novel CBIR system, which utilizes visual contents…

计算机视觉与模式识别 · 计算机科学 2017-03-23 I. M. El-Henawy , Kareem Ahmed

Content-based image retrieval (CBIR) is one of the most active research areas in multimedia information retrieval. Given a query image, the task is to search relevant images in a repository. Low level features like color, texture, and shape…

计算机视觉与模式识别 · 计算机科学 2018-12-12 Asheet Kumar , Shivam Choudhary , Vaibhav Singh Khokhar , Vikas Meena , Chiranjoy Chattopadhyay

The scalability, as well as the effectiveness, of the different Content-based Image Retrieval (CBIR) approaches proposed in literature, is today an important research issue. Given the wealth of images on the Web, CBIR systems must in fact…

Composed Image Retrieval (CIR) retrieves target images using a reference image paired with modification text. Despite rapid advances, all existing methods and datasets operate at the image level -- a single reference image plus modification…

计算机视觉与模式识别 · 计算机科学 2026-04-14 Peng Yuan , Bingyin Mei , Hui Zhang

Basic group of visual techniques such as color, shape, texture are used in Content Based Image Retrievals (CBIR) to retrieve query image or subregion of image to find similar images in image database. To improve query result, relevance…

计算机视觉与模式识别 · 计算机科学 2015-08-28 Mohini P. Sardey , G. K. Kharate

The social media explosion has populated the Internet with a wealth of images. There are two existing paradigms for image retrieval: 1) content-based image retrieval (CBIR), which has traditionally used visual features for similarity search…

多媒体 · 计算机科学 2019-09-04 Sreyasi Nag Chowdhury , Niket Tandon , Hakan Ferhatosmanoglu , Gerhard Weikum

Content-Based Image Retrieval (CBIR) locates, retrieves and displays images alike to one given as a query, using a set of features. It demands accessible data in medical archives and from medical equipment, to infer meaning after some…

计算机视觉与模式识别 · 计算机科学 2016-10-11 Albany E. Herrmann , Vania Vieira Estrela

Jewellery item retrieval is regularly used to find what people want on online marketplaces using a sample query reference image. Considering recent developments, due to the simultaneous nature of various jewelry items, various jewelry…

计算机视觉与模式识别 · 计算机科学 2023-05-15 Amin Muhammad Shoib , Summaira Jabeen , Changbo Wang , Tassawar Ali

Due to an increase in the number of image achieves, Content-Based Image Retrieval (CBIR) has gained attention for research community of computer vision. The image visual contents are represented in a feature space in the form of numerical…

计算机视觉与模式识别 · 计算机科学 2018-12-03 Atif Nazir , Kashif Nazir

Content Based Image Retrieval(CBIR) is one of the important subfield in the field of Information Retrieval. The goal of a CBIR algorithm is to retrieve semantically similar images in response to a query image submitted by the end user. CBIR…

信息检索 · 计算机科学 2014-09-03 Vikas Verma

Content-based image retrieval (CBIR) has the potential to significantly improve diagnostic aid and medical research in radiology. However, current CBIR systems face limitations due to their specialization to certain pathologies, limiting…

Content-based image retrieval (CBIR) is a task of retrieving images from their contents. Since retrieval process is a time-consuming task in large image databases, acceleration methods can be very useful. This paper presents a novel method…

图像与视频处理 · 电气工程与系统科学 2019-12-24 Sadegh Fadaei , Abdolreza Rashno , Elyas Rashno

The present research scholars are having keen interest in doing their research activities in the area of Data mining all over the world. Especially, [13]Mining Image data is the one of the essential features in this present scenario since…

计算机视觉与模式识别 · 计算机科学 2010-12-02 A. Kannan , V. Mohan , N. Anbazhagan

The advent of large scale multimedia databases has led to great challenges in content-based image retrieval (CBIR). Even though CBIR is considered an emerging field of research, however it constitutes a strong background for new…

计算机视觉与模式识别 · 计算机科学 2010-12-24 Nadia Baaziz , Omar Abahmane , Rokia Missaoui

In recent years a vast amount of visual content has been generated and shared from many fields, such as social media platforms, medical imaging, and robotics. This abundance of content creation and sharing has introduced new challenges,…

计算机视觉与模式识别 · 计算机科学 2022-11-01 Wei Chen , Yu Liu , Weiping Wang , Erwin Bakker , Theodoros Georgiou , Paul Fieguth , Li Liu , Michael S. Lew
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