Content Based Image Retrieval (CBIR) by Statistical Methods

Content Based Image Retrieval (CBIR) by Statistical Methods

An image retrieval system is a computer system for browsing, looking and recovering pictures from a huge database of advanced pictures. The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases, a specified number of images similar in visua...

Full description

Bibliographic Details
Main Author:	Fathala Ali et al.
Format:	Article
Language:	Arabic
Published:	College of Science for Women, University of Baghdad 2020-06-01
Series:	Baghdad Science Journal
Subjects:	Content Based Image Retrieval, Histogram statistical characteristics,Test of- T, Trademark Image Retrieval
Online Access:	http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/4212

Similar Items

Image Slicing and Statistical Layer Approaches for Content-Based Image Retrieval
by: Al-Nihoud, Jehad Qubiel Odeh
Published: (2004)

Correlated Primary Visual Texton Histogram Features for Content Base Image Retrieval
by: Ahmad Raza, et al.
Published: (2018-01-01)

Learning global image representation with generalized‐mean pooling and smoothed average precision for large‐scale CBIR
by: Jinliang Yao, et al.
Published: (2023-07-01)

İçerik Tabanlı Görüntü Erişimi / Content-Based Image Retrieval
by: İrem Soydal, et al.
Published: (2005-10-01)

Statistical Approach for Image Retrieval
by: Khor, Siak Wang
Published: (2007)

AUTOMATIC CHARACTERIZATION OF NEEDLEPUNCHED FELTS BY CONTENT BASED IMAGE RETRIEVAL - CBIR
by: BELINO Nuno, et al.
Published: (2018-05-01)

Improved framework of image representation for content-based image retrieval /
by: Abdalrahman Mohammed Alamin Abuelgasim, 1976-, author, et al.
Published: (2016)

Improved framework of image representation for content-based image retrieval /
by: Abdalrahman Mohammed Alamin Abuelgasim, 1976-, author
Published: (2016)

A Proposal of an Efficient Feature Extracting Method for Content-Based Image Retrieval
by: Israa Tahseen Ali, et al.
Published: (2016-06-01)

Content-based image retrieval system for plant leaf database using texture
by: Hussein, Ahmed Naser
Published: (2011)

A Novel Trademark Image Retrieval System Based on Multi-Feature Extraction and Deep Networks
by: Sandra Jardim, et al.
Published: (2022-09-01)

SIFT applied to CBIR
by: ALMEIDA, J., et al.
Published: (2009-12-01)

System refinement for content based satellite image retrieval
by: NourElDin Laban, et al.
Published: (2012-06-01)

Medical Image Registration Based Retrieval
by: Swarnambiga AYYACHAMY, et al.
Published: (2013-02-01)

Content-based image retrieval through extended normalised ridgelet-fourier and multi-resolution joint auto correlograms
by: Mustaffa, Mas Rina
Published: (2011)

Assessing challenges and rate of matching Content Retrieval Conformity with Images in Scientific Databases
by: Adel Soleimani Nezhad, et al.
Published: (2019-12-01)

Content-Based Image Retrieval: A Survey on Local and Global Features Selection, Extraction, Representation, and Evaluation Parameters
by: Divya Srivastava, et al.
Published: (2023-01-01)

A hierarchical approach based CBIR scheme using shape, texture, and color for accelerating retrieval process
by: Sumit Kumar, et al.
Published: (2023-07-01)

Generic Graphical User Interface for CBIR Framework
by: Ali Layak
Published: (2023-12-01)

From Content-Based Image Retrieval by Shape to Image Annotation
by: MOCANU, I.
Published: (2010-11-01)

Content-Based Image Retrieval Method using the Relative Location of Multiple ROIs
by: LEE, J., et al.
Published: (2011-08-01)

CBIR-DSS: Business Decision Oriented Content-Based Recommendation Model for E-Commerce
by: Ashish Bagwari, et al.
Published: (2022-10-01)

CONTENT-BASED IMAGE RETRIEVAL USING EXPRESSION SENSITIVITY BY FUZZY INFERENCE SYSTEM
by: Sukmawati Nur Endah, et al.
Published: (2015-07-01)

Content-based Image Retrieval for Carpet E-commerce Application
by: Mehdi Reza Shahabi, et al.
Published: (2021-03-01)

COMPREHENSIVE ANALYSIS OF SOME RECENT COMPETITIVE CBIR TECHNIQUES
by: Pradnya Vikhar, et al.
Published: (2017-02-01)

Distributed image retrieval with colour and keypoint features
by: Michał Ła̧giewka, et al.
Published: (2019-10-01)

Content Based Radiographic Images Indexing and Retrieval Using Pattern Orientation Histogram
by: Abolfazl Lakdashti, et al.
Published: (2008-06-01)

Minority Costume Image Retrieval by Fusion of Color Histogram and Edge Orientation Histogram
by: Xu-mei Shen, et al.
Published: (2016-09-01)

Image retrieval using the combination of text-based and content-based algorithms
by: Hanieh Mohamadi, et al.
Published: (2013-02-01)

INTEGRATION OF SPATIAL INFORMATION WITH COLOR FOR CONTENT RETRIEVAL OF REMOTE SENSING IMAGES
by: Bikesh Kumar Singh, et al.
Published: (2010-08-01)

Using Co-occurrence and Granulometry Features for Content Based Image Retrieval
by: Lal Said, et al.
Published: (2018-04-01)

Content-based Image Retrieval using Texture and Color Features
by: Abbas Hanon AL-Asadi
Published: (2019-06-01)

Content‐based image retrieval using Gaussian–Hermite moments and firefly and grey wolf optimization
by: Yasasvy Tadepalli, et al.
Published: (2021-06-01)

Textile Retrieval Based on Image Content from CDC and Webcam Cameras in Indoor Environments
by: Oscar García-Olalla, et al.
Published: (2018-04-01)

Zernike moments-local directional pattern fusion for content-based fish species image retrieval using momentgram and hue channel colour space
by: Osman, Noorul Shuhadah
Published: (2017)

Relevance Feedback in Content Based Image Retrieval: A Review
by: Manesh B. Kokare, et al.
Published: (2011-01-01)

A deep learning fusion approach to retrieve images of People's unsafe behavior from construction sites
by: Weili Fang, et al.
Published: (2022-12-01)

Image Retrieval using One-Dimensional Color Histogram Created with Entropy
by: KILICASLAN, M., et al.
Published: (2020-05-01)

Color Image Retrieval Algorithm Fusing Color and Principal Curvatures Information
by: Haoxiang Zhang, et al.
Published: (2020-01-01)

Trademark Similarity Evaluation Using a Combination of ViT and Local Features
by: Dmitry Vesnin, et al.
Published: (2023-07-01)