SlideShare a Scribd company logo
1 of 15
Image Retrieval
2012BCS025 Pratik Sakhare
2013BIT039 Sujata Regoti
2010BCS021 Abrar Soudagar
Image Retrieval
Tools
➔GIFT
➔FIRE
➔LIRE
GNU Image Finding Tool
➔ The GIFT (the GNU Image-Finding Tool) is a Content Based Image
Retrieval System (CBIRS). It was developed Computer Vision Group
of University of Geneva.
➔ It enables you to do Query By Pictorial Examples, giving you the
opportunity to improve query results by relevance feedback. For
processing your queries the program relies entirely on the content of
the images, freeing you from the need to annotate all images before
querying the collection.
➔ The GIFT is an open framework.
➔ The GIFT comes with a tool which lets you index whole directory
GIFT..
➔ Communication protocol for client-server communication, MRML, is XML based and fully
documented (http://www.mrml.net)
➔ The purpose of MRML is to separate the client part from the server part of CBIR systems and to
create a standard method for communication between different CIBR systems.
➔ GIFT uses QBPE (Qurey By Pictorial Example) with user relevance feedback.
➔ Although GIFT is slow while indexing and testing phases. Early experiments showed results being
processed and given in days, which was not acceptable hence PicSOM was formulated.
GIFT Framework
MRML : XML based communication protocol
Ref : http://slideplayer.com/slide/9340612/
(Multimedia
Retrieval
Markup
Language)
Viper: GIFT plugin
Flexible Image Retrieval Engine
➔It is a content-based image retrieval system developed by Thomas
Deselaers with many other of Human Language Technology and Pattern
Recognition Group of RWTH Aachen University.
➔The main aim of FIRE is to investigate different image descriptors and
evaluate their performance.
➔ FIRE was developed in C++ and Python and is meant to be easily
extensible.
FIRE Online Fire Image Query : http://demo.iupr.org/cgi-bin/fire-parts.cgi
Search By Part
Lucene Image Retrieval ( LIRE )
➔LIRE is a Java library that provides a simple way to retrieve images and
photos based on color and texture characteristics.
➔LIRE creates a Lucene index of image features for content based image
retrieval (CBIR)
➔Easy to use methods for searching the index and result browsing are
provided.
➔Try Web Demo : http://demo-itec.uni-klu.ac.at/liredemo/
LIRE Features
OPEN SOURCE
POWERFUL PERFORMANCE
SOLR PLUGIN
RESEARCH DRIVEN
LIRE DEMO
It provides a simple GUI
interface for
➔ Indexing photos
➔ Searching photos
➔ Browsing the created
index
Query Firing
Query Image
References
GIFT : https://www.gnu.org/software/gift/
FIRE : http://thomas.deselaers.de/fire/
LIRE : http://www.lire-project.net/
Thank you

More Related Content

What's hot

Integrating ChatGPT with Apache Airflow
Integrating ChatGPT with Apache AirflowIntegrating ChatGPT with Apache Airflow
Integrating ChatGPT with Apache AirflowTatiana Al-Chueyr
 
automatic classification in information retrieval
automatic classification in information retrievalautomatic classification in information retrieval
automatic classification in information retrievalBasma Gamal
 
Information retrieval 7 boolean model
Information retrieval 7 boolean modelInformation retrieval 7 boolean model
Information retrieval 7 boolean modelVaibhav Khanna
 
Information retrieval introduction
Information retrieval introductionInformation retrieval introduction
Information retrieval introductionnimmyjans4
 
Neural Models for Information Retrieval
Neural Models for Information RetrievalNeural Models for Information Retrieval
Neural Models for Information RetrievalBhaskar Mitra
 
Information storage and retrieval
Information storage and  retrievalInformation storage and  retrieval
Information storage and retrievalDr. Utpal Das
 
Library networks and consortium
Library networks and consortiumLibrary networks and consortium
Library networks and consortiumSunilKumar5028
 
Z39.50: Information Retrieval protocol ppt
Z39.50: Information Retrieval protocol pptZ39.50: Information Retrieval protocol ppt
Z39.50: Information Retrieval protocol pptSUNILKUMARSINGH
 
Introduction of Knowledge Graphs
Introduction of Knowledge GraphsIntroduction of Knowledge Graphs
Introduction of Knowledge GraphsJeff Z. Pan
 
Internet of Things for Libraries
Internet of Things for LibrariesInternet of Things for Libraries
Internet of Things for LibrariesNicole Baratta
 
Introduction to Metadata
Introduction to MetadataIntroduction to Metadata
Introduction to MetadataJenn Riley
 
Introduction to Dublin Core Metadata
Introduction to Dublin Core MetadataIntroduction to Dublin Core Metadata
Introduction to Dublin Core MetadataHannes Ebner
 
Dictionaries and Tolerant Retrieval.ppt
Dictionaries and Tolerant Retrieval.pptDictionaries and Tolerant Retrieval.ppt
Dictionaries and Tolerant Retrieval.pptManimaran A
 
Information retrieval (introduction)
Information  retrieval (introduction) Information  retrieval (introduction)
Information retrieval (introduction) Primya Tamil
 

What's hot (20)

Integrating ChatGPT with Apache Airflow
Integrating ChatGPT with Apache AirflowIntegrating ChatGPT with Apache Airflow
Integrating ChatGPT with Apache Airflow
 
automatic classification in information retrieval
automatic classification in information retrievalautomatic classification in information retrieval
automatic classification in information retrieval
 
Information retrieval 7 boolean model
Information retrieval 7 boolean modelInformation retrieval 7 boolean model
Information retrieval 7 boolean model
 
Information retrieval introduction
Information retrieval introductionInformation retrieval introduction
Information retrieval introduction
 
Neural Models for Information Retrieval
Neural Models for Information RetrievalNeural Models for Information Retrieval
Neural Models for Information Retrieval
 
What is Document Indexing? A tutorial for intelligent data capture.
What is Document Indexing? A tutorial for intelligent data capture.What is Document Indexing? A tutorial for intelligent data capture.
What is Document Indexing? A tutorial for intelligent data capture.
 
Information storage and retrieval
Information storage and  retrievalInformation storage and  retrieval
Information storage and retrieval
 
Library networks and consortium
Library networks and consortiumLibrary networks and consortium
Library networks and consortium
 
CS8080 INFORMATION RETRIEVAL TECHNIQUES - IRT - UNIT - I PPT IN PDF
CS8080 INFORMATION RETRIEVAL TECHNIQUES - IRT - UNIT - I  PPT  IN PDFCS8080 INFORMATION RETRIEVAL TECHNIQUES - IRT - UNIT - I  PPT  IN PDF
CS8080 INFORMATION RETRIEVAL TECHNIQUES - IRT - UNIT - I PPT IN PDF
 
Z39.50: Information Retrieval protocol ppt
Z39.50: Information Retrieval protocol pptZ39.50: Information Retrieval protocol ppt
Z39.50: Information Retrieval protocol ppt
 
Introduction of Knowledge Graphs
Introduction of Knowledge GraphsIntroduction of Knowledge Graphs
Introduction of Knowledge Graphs
 
Internet of Things for Libraries
Internet of Things for LibrariesInternet of Things for Libraries
Internet of Things for Libraries
 
Introduction to Metadata
Introduction to MetadataIntroduction to Metadata
Introduction to Metadata
 
Graph Analytics
Graph AnalyticsGraph Analytics
Graph Analytics
 
CS8080 IRT UNIT I NOTES.pdf
CS8080 IRT UNIT I  NOTES.pdfCS8080 IRT UNIT I  NOTES.pdf
CS8080 IRT UNIT I NOTES.pdf
 
Introduction to Dublin Core Metadata
Introduction to Dublin Core MetadataIntroduction to Dublin Core Metadata
Introduction to Dublin Core Metadata
 
Dictionaries and Tolerant Retrieval.ppt
Dictionaries and Tolerant Retrieval.pptDictionaries and Tolerant Retrieval.ppt
Dictionaries and Tolerant Retrieval.ppt
 
Library portal by Gaurav Boudh
Library portal by Gaurav BoudhLibrary portal by Gaurav Boudh
Library portal by Gaurav Boudh
 
OAI-PMH
OAI-PMHOAI-PMH
OAI-PMH
 
Information retrieval (introduction)
Information  retrieval (introduction) Information  retrieval (introduction)
Information retrieval (introduction)
 

Viewers also liked

Content Based Image Retrieval
Content Based Image RetrievalContent Based Image Retrieval
Content Based Image RetrievalAman Patel
 
Need for Software Engineering
Need for Software EngineeringNeed for Software Engineering
Need for Software EngineeringUpekha Vandebona
 
Multimedia content based retrieval in digital libraries
Multimedia content based retrieval in digital librariesMultimedia content based retrieval in digital libraries
Multimedia content based retrieval in digital librariesMazin Alwaaly
 
Literature Review on Content Based Image Retrieval
Literature Review on Content Based Image RetrievalLiterature Review on Content Based Image Retrieval
Literature Review on Content Based Image RetrievalUpekha Vandebona
 
CBIR For Medical Imaging...
CBIR For Medical  Imaging...CBIR For Medical  Imaging...
CBIR For Medical Imaging...Isha Sharma
 
Pattern recognition voice biometrics
Pattern recognition voice biometricsPattern recognition voice biometrics
Pattern recognition voice biometricsMazin Alwaaly
 
Content Based Image and Video Retrieval Algorithm
Content Based Image and Video Retrieval AlgorithmContent Based Image and Video Retrieval Algorithm
Content Based Image and Video Retrieval AlgorithmAkshit Bum
 
Cbir final ppt
Cbir final pptCbir final ppt
Cbir final pptrinki nag
 
Content based image retrieval
Content based image retrievalContent based image retrieval
Content based image retrievalrubaiyat11
 
Content Based Image Retrieval
Content Based Image RetrievalContent Based Image Retrieval
Content Based Image RetrievalPrem kumar
 
Content based image retrieval (cbir) using
Content based image retrieval (cbir) usingContent based image retrieval (cbir) using
Content based image retrieval (cbir) usingijcsity
 
Content Based Image Retrieval
Content Based Image RetrievalContent Based Image Retrieval
Content Based Image RetrievalSOURAV KAR
 
Content Based Image Retrieval
Content Based Image Retrieval Content Based Image Retrieval
Content Based Image Retrieval Swati Chauhan
 
Content based image retrieval using clustering Algorithm(CBIR)
Content based image retrieval using clustering Algorithm(CBIR)Content based image retrieval using clustering Algorithm(CBIR)
Content based image retrieval using clustering Algorithm(CBIR)Raja Sekar
 
Content-Based Image Retrieval (D2L6 Insight@DCU Machine Learning Workshop 2017)
Content-Based Image Retrieval (D2L6 Insight@DCU Machine Learning Workshop 2017)Content-Based Image Retrieval (D2L6 Insight@DCU Machine Learning Workshop 2017)
Content-Based Image Retrieval (D2L6 Insight@DCU Machine Learning Workshop 2017)Universitat Politècnica de Catalunya
 

Viewers also liked (20)

Content Based Image Retrieval
Content Based Image RetrievalContent Based Image Retrieval
Content Based Image Retrieval
 
Need for Software Engineering
Need for Software EngineeringNeed for Software Engineering
Need for Software Engineering
 
Multimedia content based retrieval in digital libraries
Multimedia content based retrieval in digital librariesMultimedia content based retrieval in digital libraries
Multimedia content based retrieval in digital libraries
 
Literature Review on Content Based Image Retrieval
Literature Review on Content Based Image RetrievalLiterature Review on Content Based Image Retrieval
Literature Review on Content Based Image Retrieval
 
CBIR For Medical Imaging...
CBIR For Medical  Imaging...CBIR For Medical  Imaging...
CBIR For Medical Imaging...
 
Pattern recognition voice biometrics
Pattern recognition voice biometricsPattern recognition voice biometrics
Pattern recognition voice biometrics
 
Cbir ‐ features
Cbir ‐ featuresCbir ‐ features
Cbir ‐ features
 
Content Based Image and Video Retrieval Algorithm
Content Based Image and Video Retrieval AlgorithmContent Based Image and Video Retrieval Algorithm
Content Based Image and Video Retrieval Algorithm
 
CBIR
CBIRCBIR
CBIR
 
Cbir final ppt
Cbir final pptCbir final ppt
Cbir final ppt
 
Content-based Image Retrieval
Content-based Image RetrievalContent-based Image Retrieval
Content-based Image Retrieval
 
Ga
GaGa
Ga
 
Content based image retrieval
Content based image retrievalContent based image retrieval
Content based image retrieval
 
Content Based Image Retrieval
Content Based Image RetrievalContent Based Image Retrieval
Content Based Image Retrieval
 
Content based image retrieval (cbir) using
Content based image retrieval (cbir) usingContent based image retrieval (cbir) using
Content based image retrieval (cbir) using
 
Content Based Image Retrieval
Content Based Image RetrievalContent Based Image Retrieval
Content Based Image Retrieval
 
Content Based Image Retrieval
Content Based Image Retrieval Content Based Image Retrieval
Content Based Image Retrieval
 
Content based image retrieval using clustering Algorithm(CBIR)
Content based image retrieval using clustering Algorithm(CBIR)Content based image retrieval using clustering Algorithm(CBIR)
Content based image retrieval using clustering Algorithm(CBIR)
 
CBIR
CBIRCBIR
CBIR
 
Content-Based Image Retrieval (D2L6 Insight@DCU Machine Learning Workshop 2017)
Content-Based Image Retrieval (D2L6 Insight@DCU Machine Learning Workshop 2017)Content-Based Image Retrieval (D2L6 Insight@DCU Machine Learning Workshop 2017)
Content-Based Image Retrieval (D2L6 Insight@DCU Machine Learning Workshop 2017)
 

Similar to Image retrieval

Web crawler with email extractor and image extractor
Web crawler with email extractor and image extractorWeb crawler with email extractor and image extractor
Web crawler with email extractor and image extractorAbhinav Gupta
 
Image processing project list for java and dotnet
Image processing project list for java and dotnetImage processing project list for java and dotnet
Image processing project list for java and dotnetredpel dot com
 
IRJET- Object Detection in an Image using Convolutional Neural Network
IRJET- Object Detection in an Image using Convolutional Neural NetworkIRJET- Object Detection in an Image using Convolutional Neural Network
IRJET- Object Detection in an Image using Convolutional Neural NetworkIRJET Journal
 
Improving computer vision models at scale presentation
Improving computer vision models at scale presentationImproving computer vision models at scale presentation
Improving computer vision models at scale presentationDr. Mirko Kämpf
 
Improving computer vision models at scale presentation
Improving computer vision models at scale presentationImproving computer vision models at scale presentation
Improving computer vision models at scale presentationJan Kunigk
 
01 foundations
01 foundations01 foundations
01 foundationsankit_ppt
 
Challenges of Deep Learning in Computer Vision Webinar - Tessellate Imaging
Challenges of Deep Learning in Computer Vision Webinar - Tessellate ImagingChallenges of Deep Learning in Computer Vision Webinar - Tessellate Imaging
Challenges of Deep Learning in Computer Vision Webinar - Tessellate ImagingAdhesh Shrivastava
 
Real Time Moving Object Detection for Day-Night Surveillance using AI
Real Time Moving Object Detection for Day-Night Surveillance using AIReal Time Moving Object Detection for Day-Night Surveillance using AI
Real Time Moving Object Detection for Day-Night Surveillance using AIIRJET Journal
 
Building a Custom Vision Model
Building a Custom Vision ModelBuilding a Custom Vision Model
Building a Custom Vision ModelNicholas Toscano
 
Computer Vision di Era Industri 4.0
Computer Vision di Era Industri 4.0Computer Vision di Era Industri 4.0
Computer Vision di Era Industri 4.0Achmad Solichin
 
Content based image retrieval Projects.pdf
Content based image retrieval Projects.pdfContent based image retrieval Projects.pdf
Content based image retrieval Projects.pdfrupaymts
 
Easily find your conference pictures using the power of the cloud @ Devoxx BE...
Easily find your conference pictures using the power of the cloud @ Devoxx BE...Easily find your conference pictures using the power of the cloud @ Devoxx BE...
Easily find your conference pictures using the power of the cloud @ Devoxx BE...Tim van Eijndhoven
 
Easily find your conference pictures using the power of the cloud
Easily find your conference pictures using the power of the cloudEasily find your conference pictures using the power of the cloud
Easily find your conference pictures using the power of the cloudRoy Braam
 
Multivariate feature descriptor based cbir model to query large image databases
Multivariate feature descriptor based cbir model to query large image databasesMultivariate feature descriptor based cbir model to query large image databases
Multivariate feature descriptor based cbir model to query large image databasesIJARIIT
 
COMPRO- WEB ALBUM & MOTION ANALYZER
COMPRO- WEB ALBUM  & MOTION ANALYZERCOMPRO- WEB ALBUM  & MOTION ANALYZER
COMPRO- WEB ALBUM & MOTION ANALYZERAshish Tanwer
 

Similar to Image retrieval (20)

Web crawler with email extractor and image extractor
Web crawler with email extractor and image extractorWeb crawler with email extractor and image extractor
Web crawler with email extractor and image extractor
 
Image processing project list for java and dotnet
Image processing project list for java and dotnetImage processing project list for java and dotnet
Image processing project list for java and dotnet
 
CV machine learning freelancer
CV machine learning freelancerCV machine learning freelancer
CV machine learning freelancer
 
IRJET- Object Detection in an Image using Convolutional Neural Network
IRJET- Object Detection in an Image using Convolutional Neural NetworkIRJET- Object Detection in an Image using Convolutional Neural Network
IRJET- Object Detection in an Image using Convolutional Neural Network
 
Improving computer vision models at scale presentation
Improving computer vision models at scale presentationImproving computer vision models at scale presentation
Improving computer vision models at scale presentation
 
Improving computer vision models at scale presentation
Improving computer vision models at scale presentationImproving computer vision models at scale presentation
Improving computer vision models at scale presentation
 
journal in research
journal in research journal in research
journal in research
 
journal published
journal publishedjournal published
journal published
 
01 foundations
01 foundations01 foundations
01 foundations
 
Challenges of Deep Learning in Computer Vision Webinar - Tessellate Imaging
Challenges of Deep Learning in Computer Vision Webinar - Tessellate ImagingChallenges of Deep Learning in Computer Vision Webinar - Tessellate Imaging
Challenges of Deep Learning in Computer Vision Webinar - Tessellate Imaging
 
F04402038042
F04402038042F04402038042
F04402038042
 
Real Time Moving Object Detection for Day-Night Surveillance using AI
Real Time Moving Object Detection for Day-Night Surveillance using AIReal Time Moving Object Detection for Day-Night Surveillance using AI
Real Time Moving Object Detection for Day-Night Surveillance using AI
 
Building a Custom Vision Model
Building a Custom Vision ModelBuilding a Custom Vision Model
Building a Custom Vision Model
 
Computer Vision di Era Industri 4.0
Computer Vision di Era Industri 4.0Computer Vision di Era Industri 4.0
Computer Vision di Era Industri 4.0
 
Content based image retrieval Projects.pdf
Content based image retrieval Projects.pdfContent based image retrieval Projects.pdf
Content based image retrieval Projects.pdf
 
Easily find your conference pictures using the power of the cloud @ Devoxx BE...
Easily find your conference pictures using the power of the cloud @ Devoxx BE...Easily find your conference pictures using the power of the cloud @ Devoxx BE...
Easily find your conference pictures using the power of the cloud @ Devoxx BE...
 
Easily find your conference pictures using the power of the cloud
Easily find your conference pictures using the power of the cloudEasily find your conference pictures using the power of the cloud
Easily find your conference pictures using the power of the cloud
 
EJC'12
EJC'12EJC'12
EJC'12
 
Multivariate feature descriptor based cbir model to query large image databases
Multivariate feature descriptor based cbir model to query large image databasesMultivariate feature descriptor based cbir model to query large image databases
Multivariate feature descriptor based cbir model to query large image databases
 
COMPRO- WEB ALBUM & MOTION ANALYZER
COMPRO- WEB ALBUM  & MOTION ANALYZERCOMPRO- WEB ALBUM  & MOTION ANALYZER
COMPRO- WEB ALBUM & MOTION ANALYZER
 

More from Sujata Regoti

Social media connecting or disconnecting
Social media connecting or disconnectingSocial media connecting or disconnecting
Social media connecting or disconnectingSujata Regoti
 
Servlet and jsp interview questions
Servlet and jsp interview questionsServlet and jsp interview questions
Servlet and jsp interview questionsSujata Regoti
 
Git,Github,How to host using Github
Git,Github,How to host using GithubGit,Github,How to host using Github
Git,Github,How to host using GithubSujata Regoti
 
Technical aptitude test 2 CSE
Technical aptitude test 2 CSETechnical aptitude test 2 CSE
Technical aptitude test 2 CSESujata Regoti
 
Technical aptitude Test 1 CSE
Technical aptitude Test 1 CSETechnical aptitude Test 1 CSE
Technical aptitude Test 1 CSESujata Regoti
 

More from Sujata Regoti (9)

Social media connecting or disconnecting
Social media connecting or disconnectingSocial media connecting or disconnecting
Social media connecting or disconnecting
 
Key management
Key managementKey management
Key management
 
Web mining tools
Web mining toolsWeb mining tools
Web mining tools
 
Servlet and jsp interview questions
Servlet and jsp interview questionsServlet and jsp interview questions
Servlet and jsp interview questions
 
Git,Github,How to host using Github
Git,Github,How to host using GithubGit,Github,How to host using Github
Git,Github,How to host using Github
 
Technical aptitude test 2 CSE
Technical aptitude test 2 CSETechnical aptitude test 2 CSE
Technical aptitude test 2 CSE
 
Technical aptitude Test 1 CSE
Technical aptitude Test 1 CSETechnical aptitude Test 1 CSE
Technical aptitude Test 1 CSE
 
Big Data
Big DataBig Data
Big Data
 
Inflation measuring
Inflation measuringInflation measuring
Inflation measuring
 

Recently uploaded

"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr LapshynFwdays
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDGMarianaLemus7
 
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024BookNet Canada
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Wonjun Hwang
 
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024BookNet Canada
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptxLBM Solutions
 
Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsSnow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsHyundai Motor Group
 
Science&tech:THE INFORMATION AGE STS.pdf
Science&tech:THE INFORMATION AGE STS.pdfScience&tech:THE INFORMATION AGE STS.pdf
Science&tech:THE INFORMATION AGE STS.pdfjimielynbastida
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):comworks
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraDeakin University
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxnull - The Open Security Community
 

Recently uploaded (20)

"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDG
 
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
 
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping Elbows
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptx
 
Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsSnow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
 
Science&tech:THE INFORMATION AGE STS.pdf
Science&tech:THE INFORMATION AGE STS.pdfScience&tech:THE INFORMATION AGE STS.pdf
Science&tech:THE INFORMATION AGE STS.pdf
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
 
Hot Sexy call girls in Panjabi Bagh 🔝 9953056974 🔝 Delhi escort Service
Hot Sexy call girls in Panjabi Bagh 🔝 9953056974 🔝 Delhi escort ServiceHot Sexy call girls in Panjabi Bagh 🔝 9953056974 🔝 Delhi escort Service
Hot Sexy call girls in Panjabi Bagh 🔝 9953056974 🔝 Delhi escort Service
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning era
 
The transition to renewables in India.pdf
The transition to renewables in India.pdfThe transition to renewables in India.pdf
The transition to renewables in India.pdf
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
 

Image retrieval

  • 1. Image Retrieval 2012BCS025 Pratik Sakhare 2013BIT039 Sujata Regoti 2010BCS021 Abrar Soudagar
  • 3. GNU Image Finding Tool ➔ The GIFT (the GNU Image-Finding Tool) is a Content Based Image Retrieval System (CBIRS). It was developed Computer Vision Group of University of Geneva. ➔ It enables you to do Query By Pictorial Examples, giving you the opportunity to improve query results by relevance feedback. For processing your queries the program relies entirely on the content of the images, freeing you from the need to annotate all images before querying the collection. ➔ The GIFT is an open framework. ➔ The GIFT comes with a tool which lets you index whole directory
  • 4. GIFT.. ➔ Communication protocol for client-server communication, MRML, is XML based and fully documented (http://www.mrml.net) ➔ The purpose of MRML is to separate the client part from the server part of CBIR systems and to create a standard method for communication between different CIBR systems. ➔ GIFT uses QBPE (Qurey By Pictorial Example) with user relevance feedback. ➔ Although GIFT is slow while indexing and testing phases. Early experiments showed results being processed and given in days, which was not acceptable hence PicSOM was formulated.
  • 5. GIFT Framework MRML : XML based communication protocol Ref : http://slideplayer.com/slide/9340612/ (Multimedia Retrieval Markup Language)
  • 7. Flexible Image Retrieval Engine ➔It is a content-based image retrieval system developed by Thomas Deselaers with many other of Human Language Technology and Pattern Recognition Group of RWTH Aachen University. ➔The main aim of FIRE is to investigate different image descriptors and evaluate their performance. ➔ FIRE was developed in C++ and Python and is meant to be easily extensible.
  • 8. FIRE Online Fire Image Query : http://demo.iupr.org/cgi-bin/fire-parts.cgi
  • 10. Lucene Image Retrieval ( LIRE ) ➔LIRE is a Java library that provides a simple way to retrieve images and photos based on color and texture characteristics. ➔LIRE creates a Lucene index of image features for content based image retrieval (CBIR) ➔Easy to use methods for searching the index and result browsing are provided. ➔Try Web Demo : http://demo-itec.uni-klu.ac.at/liredemo/
  • 11. LIRE Features OPEN SOURCE POWERFUL PERFORMANCE SOLR PLUGIN RESEARCH DRIVEN
  • 12. LIRE DEMO It provides a simple GUI interface for ➔ Indexing photos ➔ Searching photos ➔ Browsing the created index
  • 14. References GIFT : https://www.gnu.org/software/gift/ FIRE : http://thomas.deselaers.de/fire/ LIRE : http://www.lire-project.net/