cbir for sketches in image processing


cbir for sketches in image processing

Sketch Based Image Retrieval Approach Using Gray Level Co-Occurrence Matrix
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KN Reddy, PP Kumari ,International Journal of Science and , 2012 ,ijsea.com
 Abstract: This work focuses on Content Based Image Retrieval (CBIR) system using
sketches, which is one of the most accepted, rising research areas of the digital image
processing. The majority of the available image searching 

 A Content Based Image Retrieval System Using Graphs
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DTVD Rao, BHA Laxmi ,2012 ,ijair.jctjournals.com
 problems and challenges concerned with the design and the creation of CBIR systems  Keywords:
content-based image retrieval, image database, query by sketch, matching, similarity I  since it
must be done manually or at best semi-automatically; image processing technology is 

 A Refined Hybrid Image Retrieval System using Text and Color
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N Goel, P Sehgal ,2012
 Another system Sketch4Match uses color as the feature descriptor for matching of
a sketch with the corresponding image [16]. CBIR gives better result where application
contains more of visual content rather than semantic content. 

Large Scale Sketch Based Image Retrieval Using Patch Hashing
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 sketches can be described only by their shape and spatial configuration, therefore traditional
CBIR meth- ods  Hu, R., Wang, T., Collomosse, J.: A bag-of-regions approach to sketch-based
image retrieval  In: 2011 18th IEEE International Conference on Image Processing, ICIP, pp 

 Iconic Visual Queries for Face Image Retrieval
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 It is evident that the proposed user interaction strategy is more useful as part of a more functional
system for CBIR.  5:1–5:59, April 2008. [3] T. Hisamori, and G. Ohashi, Query-by-sketch interactive
image retrieval using rough sets, IEEE Int. Conf.  Conf. Image Processing, 1998. 

 Content Based Image Retrieval: Survey
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M Rehman, M Iqbal, M Sharif, M Raza ,World Applied Sciences Journal, 2012
 Precision-scope curve query-by-example QBE and query-by-sketch QBS can be implemented
by many developers is used to evaluate addressed by a specialized query language designed
for image retrieval performance [84].  CBIR. Using multiscale color coherent vector, the 

Comparative Study and Optimization of Feature-Extraction Techniques for Content based ImageRetrieval
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 related techniques to derive retrieval features is referred to as Content-Based Image Retrieval
(CBIR).  are web media search engines that follow the ‘query by similar image’ paradigm. 
ElasticElastic matching of images [1] for sketch-based IR, windowed search over location and 

 Comparison and Analysis of Content Based Image Retrieval Systems Based On Relevance Feedback
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L Pinjarkar, M Sharma, K Mehta ,Journal of Emerging Trends in , 2012
 similarities /distances between the feature vectors of the query example or sketch and those  of
the standard evaluation parameters used for evaluation of the CBIR system which  Framework,
Feature Sub spaces, and Progressive LearningIEEE Trans.on Image processing, Vol. 

 Novel Approach for Color based Comic Image Segmentation for Extraction of Text using Modify Fuzzy Possiblistic C-Means Clustering Algorithm
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M Praneesh, RJ Kumar , Issue on Information Processing , 2012
 to view in dark and bright portion of the image and linear sketch model is  Tarzjan and HA
Moghaddam, A Novel Evolutionary Approach for Optimizing Content-Based Image Indexing
Algorithms  10] S. Cheng, W. Huang, Y. Liao and D. Wu, A Parallel CBIR Implementation Using 

A Shape-Based Two-Stage Product Image Retrieval Method
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SF Gong, J Du ,Advanced Materials Research, 2012 ,Trans Tech Publ
 Generally, the application of CBIR technology in E-Commerce is still a novel area and  level of
Th, where Th = 0.35, outperforms with salient edges which properly sketch contours of  to image
database and a filter selection strategy to reduce the image processing computation. 

 A System Which Retrieves Images Using a Query Image
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ME Erva, MKC Shekar ,International Journal of Engineering, 2012 ,ijert.org
 Currently, CBIR routines are relatively adept at identifying color and texture distributions, as well
as primitive  Content based image retrieval: an application to tattoo images, IEEE International
Conference on Image Processing, pp.  5] AK Jain, JE Lee, and R. Jin, Sketch to photo 

Annotated free-hand sketches for video retrieval using object semantics and motion
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1835–1842 (2006) 30. Di Sciascio, E., Mingolla, G., Mongiello, M.: CBIR over the web
using query by sketch and relevance feedback. In: Proc. Intl. Conf.  Wang, C., Li, Z., Zhang, L.:
Mindfinder: image search by interactive sketching and tagging. In: WWW, pp. 

 Query by Image for Efficient Information Retrieval: A Necessity
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D Chadha, N Singh , -Cum-Conference on Recent Trends in , 2012
 H. Mülle et al. [19] described a technique for Content-based visual information retrieval (CBVIR)
or content-based image retrieval (CBIR).  Query-By-Sketch Based Image Retrieval Using Diffusion
Tensor Fields, Image Processing Theory, Tools and Applications, IEEE 2010. 

 Content Based Image Retrieval Methods Using Self Supporting Retrieval Map Algorithm
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MP Jayaprabha, R Somasundaram ,International Journal, 2012
 8]. Theframework of multi-threaded processing is proposed toincorporate an image analysis
algorithm  The query can either be example images,user- constructed sketches and drawings
or  8]. Virage 35] and Excaliburare other developers of commercial CBIR systems.Visual 

 Content Based Image Retrieval with Semantic Features using Object Ontology
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A Khodaskar, SA Ladke ,International Journal of Engineering, 2012 ,ijert.org
 The commonest approaches use the so-called Content-Based Image Retrieval (CBIR)
systems. Basically, these systems try to retrieve images similar to a user-defined
specification or pattern (eg, shape sketch, image example). 

Robust scene classification by Gist with angular radial partitioning
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 Proceedings of the 5th International Symposium on Communications, Control and Signal
Processing, ISCCSP 2012, Rome, Italy, 2-4 May 2012  ARP has been successfully applied in
content-based image retrieval (CBIR), sketch-based image retrieval (SBIR) applications 

Efficient Image Retrieval Based on Texture Features Using Concept of Histogram
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DA Sadineni, VR Pokala, P Rajesh ,Global Journal of , 2012 ,computerresearch.org
 allows users to formulate queries by submitting an example of the type of image being sought,
though some offer alternatives such as selection from a palette or sketch input.  Approaches of
CBIR d)  In International Conference on Image Processing (ICIP), pages 568–571, Oct. 

 Design, Implementation and Evaluation of Two Medical Content based Image Retrieval Systems
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 In order to fully exploit the potential of the Matlab CBIR system and the possibility to expand it
with ad hoc algorithms we have designed a query by sketch search strategy  allows the doctor
to extract images linked to a pathology described by the region in the image affected by 

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MP Jayaprabha, DR Somasundaram ,Research Journal of Pure Algebra , 2012 ,rjpa.info
 For example user may submit a sketch, click on the texture pallet, or select a particular  This implies
that CLUE may be embedded in a typical CBIR system regardless of the imagery  Texture has
long been an important topic in image processing [7].Methods of texture analysis are 

Pill-ID: Matching and retrieval of drug pill images
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QBIC was the first functional CBIR system reported (Flickner et al., 1995). QBIC allowed
image retrieval using user-constructed sketches and drawings, selected colors and
texture patterns, or other graphical information as queries. 

 Comparative Evaluation of Image Retrieval Algorithms using Relevance Feedback and it’s Applications
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L Pinjarkar, K Mehta, M Sharma ,International Journal of , 2012
 distances between the feature vectors of the query example or sketch and those  values of the
standard evaluation parameters used for evaluation of the CBIR algorithm for  With Relevant
Feedback proceedings of IEEE International Conference on Image Processing (ICIP’2000 

 Coarse Level Sketch Based Image Retreival Using Gray Level Co-Occurance Matrix
free download

D Arundeepthi, M Narayana
 Abstract- This paper proposes a method of Content based image retrieval (CBIR) using sketches,
which is one of the most popular, rising research areas of the digital image processing. Most of
the available image search tools, such as Google Images and Yahoo! 

 Content-based Image Retrieval System Implementation Using Sketches
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DS Sagar, DP Kumar, KN Rao ,ijrct.org
 specific descriptor, which can handle the informational gap between a sketch and a colored image,
making an opportunity for the efficient search hereby .The content based image retrieval (CBIR)
is one of the most popular, rising research areas of the digital image processing. 

 Perceptual features and Content-based Image Retrieval System Implementation UsingSketches
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N Sadanandam, GJ Mary, J Gyani ,ijrct.org
 specific descriptor, which can handle the informational gap between a sketch and a colored image,
making an opportunity for the efficient search hereby .The content based image retrieval (CBIR)
is one of the most popular, rising research areas of the digital image processing. 

 Edge Histogram for Sketch Based Image Retrieval Using Contourlet Edge Detection
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AJ Joseph, VK Govindan ,irnetexplore.ac.in
 Multiscale Modeling of Images Using the Contourlet Transform, IEEE transactions on image
processing Vol.15  A Walshlet Based Approach for Color and Texture Extraction in CBIR,
Proceedings on  pp 87-91, 2012 [17] Annie Julie Joseph and VK Govidan Sketch Based Image 

 Analysis of Web Information Gathering Based on Sketch Image Retrieval System
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S Annam, M Kavitha, KCR Kumar ,ijettcs.org
 Web documents Benefits Relevance feedback is an interactive process that starts with normal
CBIR.  The objectives of system performs a test sketch-based image retrieval system, main aspects 
Her interested areas include Network Security, Image Processing, Retrieval Systems 

 3D Color Feature Extraction in Content-Based Image Retrieval
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A Komali, VS Kumar, KG Babu, ASK Ratnam ,International Journal of Soft
 The approach more frequently adopted for CBIR systems is based on the conventional color
histogram (CCH), which  boundary segments Queries to shape retrieval systems are formulated
either by identifying an example image to act as the query, or as a user-drawn sketch.