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Content based Image Retrieval for Medical Images using Canny Edge Detection Algorithm

B. Ramamurthy, K.R. Chandran
2011 International Journal of Computer Applications  
This paper aims to provide an efficient medical image data Retrieval from a huge content of medical database using one of the images content such as image shape, because, efficient content-based image  ...  The main objective of this paper is to provide an efficient tool which is used for efficient medical image retrieval from a huge content of medical image database and which is used for further medical  ...  INTRODUCTION Content based image retrieval (CBIR) is a technique in which images are indexed by extracting their low level features and image retrieval is only based upon these indexed image features.  ... 
doi:10.5120/2222-2831 fatcat:ixojrq2yrbedtj5uwzhquk7g7q

A STUDY AND SURVEY ON CONTENT-BASED IMAGE RETRIEVAL USING LOW LEVEL FEATURES FOR MOBILE DEVICES

Manjusha Y. Patil, Amol B. Kasture
2020 Samvakti Journal of Research in Information Technology  
features like color, texture and shape for efficient and accurate image retrieval on mobile devices.  ...  In Content based Image Retrieval (CBIR), images are retrieved by their visual content such as color, texture and shapes.  ...  This is an efficient method of CBIR. Relevance feedback (RF) is an efficient method for content-based image retrieval (CBIR).  ... 
doi:10.46402/202007.343.48.255 fatcat:knj6oozskne6dmgzv6s2tnmh2u

An Efficient Model for Content based Image Retrieval

M. Karthikeyan, P. Aruna
2012 International Journal of Computer Applications  
Current systems generally make use of low level features like colour, texture, and shape. In this paper, a novel approach for generalized image retrieval based on semantic contents is presented.  ...  Hence, there is a need for Content Based Image retrieval application which makes the retrieval process very efficient.  ...  The proposed system concentrates on Content Based Image retrieval method using image content descriptors colour, texture and shape for efficient retrieval of images.  ... 
doi:10.5120/5665-7698 fatcat:qthds4u64nfyrg6sgekn6remta

An Efficient Image Retrieval Based on Fusion of Fast Features and Query Image Classification

Vibhav Prakash Singh, Subodh Srivastava, Rajeev Srivastava
2017 International Journal of Rough Sets and Data Analysis  
In this paper, an efficient and fast CBIR system is proposed, which is based on a fusion of computationally light weighted colour and texture features; chromaticity moment, colour percentile, and local  ...  Content Based Image Retrieval (CBIR) is an emerging research area in computer vision, in which, we yield similar images as per the query content.  ...  Usually, humans recognize an image from its colour, texture, and shape based appearances. Therefore, it is natural to use all these features for image retrieval.  ... 
doi:10.4018/ijrsda.2017010102 fatcat:b3smijnsoraurfde6dvupbvdpu

A Survey on Features and Techniques in Content Based Image Retrieval

Meenu Kalra, Pooja Handa
2015 INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY  
Content-based image retrieval (CBIR) is widely adopted method for finding images from vast collection of images in the database.  ...  Among them, content-based image retrieval systems (CBIR) have become very popular for browsing, searching and retrieving images from a large database of digital images as it requires relatively less human  ...  Content-based image retrieval [1] , uses the visual contents of an image such as color, shape, texture, and spatial layout to represent and index the image.  ... 
doi:10.24297/ijct.v14i10.1829 fatcat:76o4nhzqlremvct7kaj7jtoz7a

Multi-Feature Extraction and Matching Approach for Image Retrieval: A Review

Prof. Chopde N. R., Miss Rewaskar P. A
2017 IJARCCE  
Three important visual features of an image include Color, Texture, Frequency,color histogram is most commonly used color representation color histogram gives better retrieval accuracy.When these features  ...  Image representation based on certain features helps in retrieval process.  ...  Content-Based Image Retrieval using Color Moment and Gabor TextureFeature (IJCSI 2012) they proposed an efficient image retrieval method based on color moments and Gabor texture features.  ... 
doi:10.17148/ijarcce.2017.6174 fatcat:mpl2mb37sja7zl6y3kfg4j3cem

An Integrated approach to CBIR using multiple features and HSV Histogram

Neelima N., Sreenivasa Reddy E., Kalpitha N.
2016 International Journal of Engineering and Technology  
Rouhollah Rahmani et.al proposed [2] localized content-based image retrieval, where the user is only interested in a portion of the image, and the rest of the image is irrelevant.  ...  An efficient search for semantically relevant images has always been thirst in computer vision and processing specially in large scale image retrieval.  ...  In the field of computer vision, Local binary patterns are one of the best texture based visual descriptor.  ... 
doi:10.21817/ijet/2016/v8i5/160805401 fatcat:mdx23agjvbdvhgzglyr2jlkcni

Local bit plane adjacent neighborhood dissimilarity pattern for medical CT image retrieval

Rakcinpha Hatibaruah, Vijay Kumar Nath, Deepika Hazarika
2019 Procedia Computer Science  
In this article, new feature descriptor local bit plane adjacent neighborhood dissimilarity pattern (LBPANDP) is introduced for CT image retrieval.  ...  Abstract In this article, new feature descriptor local bit plane adjacent neighborhood dissimilarity pattern (LBPANDP) is introduced for CT image retrieval.  ...  Acknowledgements This research is supported by Digital India Corporation (formerly Media Lab Asia), Ministry of Electronics and Information Technology, Govt. of India, through VisvesvarayaPh.D scheme.  ... 
doi:10.1016/j.procs.2020.01.073 fatcat:bfcm2cnnibd7toqskx46losrte

COMPARISON STUDY BETWEEN IMAGE RETRIEVAL METHODS

Zahraa H. Al-Obaide, Ayad A. Al-Ani
2022 Iraqi Journal of Information & Communications Technology  
Content-Based Image Retrieval is a process that provides a framework for image search, and low-level visual features are commonly used to retrieve the images from the image database.  ...  The shape, color, and texture are examples of low-level image features.  ...  Both the color feature and the textural feature are used to efficiently retrieve a color image from a large database.  ... 
doi:10.31987/ijict.5.1.182 fatcat:lyeb34toqzfjneha5lv5arnkai

A new approach for content-based image retrieval for medical applications using low-level image descriptors

Mohammed Qassim Shatnawi, Mohammad Alrousan, Suzan Amareen
2020 International Journal of Electrical and Computer Engineering (IJECE)  
<p>Content based image retrieval (CBIR) has become an important factor in medical imaging research and is obtaining a great success.  ...  The final results showed a qualified system in medical images retrieval specially that the low-level image descriptors have not been used yet in the image similarity matching in the medical field.</p>  ...  Content based image retrieval (CBIR) means that images can be searched by their visual content, such as graph, text, color [1] , and local and global features [2] .  ... 
doi:10.11591/ijece.v10i4.pp4363-4371 fatcat:pnhgdf5hijddlj7sj2da4hig2e

A Review on Image Retrieval Techniques

M.S. Meharban, Dr.S. Priya
2016 Bonfring International Journal of Advances in Image Processing  
Content Based Image Retrieval (CBIR) is one of the image retrieval techniques which use visual features of an image such as color, shape, and texture features etc.  ...  So in the present situation content based image retrieval is becoming necessary for exact and fast image retrieval.  ...  Content Based Image Retrieval is also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR).  ... 
doi:10.9756/bijaip.8136 fatcat:xx7qitoxjfb4rnxuedxcbkcgim

An Efficient Technique for Image Retrieval from the Large Database on the Basis of Color and Texture

Mayank Jain, Divakar Singh
2016 International Journal of Computer Applications  
CBIR technique uses the visual contents like as color, shape and texture that are called features, to searching, browsing, and navigation of query images for large image databases.  ...  The combination of texture of red channel, green channel and blue channel we create a feature vector for all images of the database.  ...  the concept of directional local extremas and their magnitude based patterns for content based image indexing and retrieval.  ... 
doi:10.5120/ijca2016908889 fatcat:cafvaw4qxjbkvgwfx4yc2bgxna

Content based Image Retrieval using Local Patterns: A Survey

V . Uma Maheswari, Dr. Premasudha B. G, Dr. S. Viswanadha Raju
2016 International Journal of Engineering Research and  
The survey includes the information of local patterns covering the research aspects of image feature extraction which is the most fundamental and prominent base of CBIR.  ...  Paper presents a survey on the technical achievements of Content Based Image Retrieval (CBIR), this area is been active from past two decades.  ...  To overcome these problems an automatic, efficient, smart system is needed named content based image retrieval.  ... 
doi:10.17577/ijertv5is100338 fatcat:ts4omx26hbaqroidr7j73re36e

An intelligent content-based image retrieval system for clinical decision support in brain tumor diagnosis

Megha P. Arakeri, G. Ram Mohana Reddy
2013 International Journal of Multimedia Information Retrieval  
Accordingly in this paper, we propose an intelligent content-based image retrieval (CBIR) system which retrieves similar pathology bearing magnetic resonance (MR) images of the brain from a medical database  ...  In order to provide faster image retrieval, we propose an indexing method called clustering with principal component analysis (PCA) and KD-tree which groups subclass features into clusters using modified  ...  Acknowledgments The authors wish to thank the anonymous reviewers for the useful and valuable suggestions.  ... 
doi:10.1007/s13735-013-0037-5 fatcat:liqlh7jrmjbmfnfe7qrosf7b7a

A Universal Model For Content-Based Image Retrieval

S. Nandagopalan, Dr. B. S. Adiga, N. Deepak
2008 Zenodo  
A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency.  ...  In this paper a novel approach for generalized image retrieval based on semantic contents is presented.  ...  Content Based Image Retrieval (CBIR) is a technique which uses visual contents, normally called as features, to search images from large scale image databases according to users' requests in the form of  ... 
doi:10.5281/zenodo.1072762 fatcat:uoq3jtyzlrewzbicvn57cddocy
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