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Feature integration and relevance feedback analysis in image similarity evaluation

Eugenio Di Sciascio
1998 Journal of Electronic Imaging (JEI)  
.H\ZRUGV image feature computation, retrieval by image content, vector space model, Hough transform, relevance feedback.  ...  In this paper we describe the results of a study on similarity evaluation in image retrieval using color, object orientation and relative position as content features, in a framework oriented to image  ...  important issue, and the use of a technique similar to the vector space approach used in text-based information retrieval, that allows us to increase relevant image accuracy using relevance feedback analysis  ... 
doi:10.1117/1.482646 fatcat:wgkmcie52re4hibg26cblyk6xe

Content-based image retrieval using optimal feature combination and relevance feedback

Lijun Zhao, Jiakui Tang
2010 2010 International Conference on Computer Application and System Modeling (ICCASM 2010)  
In order to narrow the gap between user query concept and low-level features in CBIR, a multi-round relevance feedback (RF) strategy based on both support vector machine (SVM) and feature similarity is  ...  With the rapid development o f the multimedia technology and Internet, content-based image retrieval (CBIR) has become an active research field at present.  ...  Feature Similarity Measurement The commonly used similarity measure method is the vector space model, in which they regard the features of an image as a point in the vector space, through calculating the  ... 
doi:10.1109/iccasm.2010.5620791 fatcat:wffoe3vq2jdrhjdza2tzu3ma4u

Opponent Color And Curvelet Transform Based Image Retrieval System Using Genetic Algorithm

Yesubai Rubavathi Charles, Ravi Ramraj
2015 Zenodo  
Thus, the experimental results confirm that the proposed content based image retrieval system architecture attains better solution for image retrieval.  ...  Extensive and comparative experiments have been conducted to evaluate proposed framework for content based image retrieval on two databases, i.e., COIL-100 and Corel-1000.  ...  Based on the retrieval results, the proposed approach achieves better retrieval performance in the YC b C r space on Corel dataset.  ... 
doi:10.5281/zenodo.1110855 fatcat:brbdlrlpwvbftenhvblwsjqery

Survey On Content Based Image Retrieval

Anuradha Shitole1
2014 Zenodo  
So searching and retrieving images in large image databases has become more challenging. From the last few years, Content Based Image Retrieval (CBIR) gained increasing attention from researcher.  ...  CBIR is a system which uses visual features of image to search user required image from large image database and user's requests in the form of a query image.  ...  Selection of similarity metrics has a direct impact on the performance of content-based image retrieval.  ... 
doi:10.5281/zenodo.1450266 fatcat:ekabvdx2rneobkpercllkmx2ha

Self-feedback image retrieval algorithm based on annular color moments

Ying Deng, Yuanhui Yu
2019 EURASIP Journal on Image and Video Processing  
To further contribute to the research, this paper proposes a self-feedback image retrieval algorithm based on annular color moments.  ...  In this approach, hashing sequences of color moments based on annular segmentation are extracted to be used as feature vectors for initial retrieval.  ...  Her research interests are image processing, pattern recognition and data mining.  ... 
doi:10.1186/s13640-018-0400-9 fatcat:kle3i5vjavbandeqghrk347i4u

Kernel-based distance metric learning for content-based image retrieval

Hong Chang, Dit-Yan Yeung
2007 Image and Vision Computing  
For a specific set of features chosen for representing images, the performance of a content-based image retrieval (CBIR) system depends critically on the similarity or dissimilarity measure used.  ...  In this paper, we propose a kernel approach to improve the retrieval performance of CBIR systems by learning a distance metric based on pairwise constraints between images as supervisory information.  ...  However, [12] and [13] are based on the assumption that the feature vectors representing the images form a Riemannian manifold in the feature space.  ... 
doi:10.1016/j.imavis.2006.05.013 fatcat:6cd3utk6tjgqhomwh5cywvuhnq

Interactive Semantic Image Retrieval

Pushpa B. Patil, Manesh B. Kokare
2013 Journal of Information Processing Systems  
Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge  ...  , based on the user interaction.  ...  We begin our discussion of support vector machines for a two-class classification problem by using linear models of the form: Where training vectors X i are mapped into a higher dimensional space by  ... 
doi:10.3745/jips.2013.9.3.349 fatcat:dugtx4nicjf6te4466nmoefcj4

Using Biased Support Vector Machine to Improve Retrieval Result in Image Retrieval with Self-organizing Map [chapter]

Chi-Hang Chan, Irwin King
2004 Lecture Notes in Computer Science  
The relevance feedback approach is a powerful technique in content-based image retrieval (CBIR) tasks.  ...  Moreover, we apply our Self-Organizing Mapbased inter-query technique to reorganize the feature vector space, in order to incorporate the information provided by past queries and improve the retrieval  ...  The model vectors m i ∈ M of neurons in the SOM are used to partition the feature vector space based on the minimum distance classifier, each image I i is classified into different groups represented by  ... 
doi:10.1007/978-3-540-30499-9_109 fatcat:ty725i53kfgaznviqd6aw53uke

Which Components Are Important For Interactive Image Searching?

Dacheng Tao, Xiaoou Tang, Xuelong Li
2009 IEEE transactions on circuits and systems for video technology (Print)  
Index Terms-Content-based image retrieval (CBIR), kernel machine, orthogonal complement component analysis (OCCA), relevance feedback (RF), support vector machine (SVM).  ...  both linear and kernel spaces when users want to retrieve images with a homogeneous concept.  ...  However, if a user mislabels too many images during the relevance feedback, the learning will be misled to an incorrect retrieval model.  ... 
doi:10.1109/tcsvt.2008.918548 fatcat:elmqcxcvbjejdfjkr6sd6cxphe

Which Components are Important for Interactive Image Searching?

Dacheng Tao, Xiaoou Tang, Xuelong Li
2008 IEEE transactions on circuits and systems for video technology (Print)  
Index Terms-Content-based image retrieval (CBIR), kernel machine, orthogonal complement component analysis (OCCA), relevance feedback (RF), support vector machine (SVM).  ...  both linear and kernel spaces when users want to retrieve images with a homogeneous concept.  ...  However, if a user mislabels too many images during the relevance feedback, the learning will be misled to an incorrect retrieval model.  ... 
doi:10.1109/tcsvt.2007.906936 fatcat:ecwqn3xfpjac7palgono3idbh4

A principal component analysis-based feature dimensionality reduction scheme for content-based image retrieval system

Oluwole A Adegbola, Ismail A Adeyemo, Folasade A Semire, Segun I. Popoola, Aderemi A Atayero
2020 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
In content-based image retrieval (CBIR) system, one approach of image representation is to employ combination of low-level visual features cascaded together into a flat vector.  ...  The PCA scheme was incorporated into a CBIR system that utilized the entire feature vector space.  ...  These properties of PCA have attracted research on PCA-based variable selection methods [7, [13] [14] [15] [16] [17] [18] and has been applied to relevance feedback in both document and image retrieval  ... 
doi:10.12928/telkomnika.v18i4.11176 fatcat:k3ah2bfa6beuzgq33agsa3cwvi

A Survey on Features and Techniques in Content Based Image Retrieval

Meenu Kalra, Pooja Handa
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  ...  GM models of the images based on a universal GM model in a Bayesian manner and information is extracted from the entire database.  ... 
doi:10.24297/ijct.v14i10.1829 fatcat:76o4nhzqlremvct7kaj7jtoz7a

Image Indexing and Retrieval in Compressed Domain Using Color Clusters

Meekal Bajaj, Jose A. lay
2007 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing  
The experimental results of the proposed model on a database of 7380 images are reported. Index Terms-Color indexing, compressed domain, content based retrieval, DCT.  ...  A compressed domain color-based image indexing method that avoids overheads associated with full decompression and color space transformation by operating in the YCbCr space has been presented.  ...  We propose a model to address this that performs retrieval within the compressed domain YCbCr color space, thus eliminating the need for repeated transformations and the associated overhead.  ... 
doi:10.1109/ciisp.2007.369180 fatcat:vctscxgvdnfslflt4fnidfcrnu

Inter-query semantic learning approach to image retrieval

Scott Fechser, Ran Chang, Xiaojun Qi
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
This paper presents an inter-query semantic learning approach for image retrieval with relevance feedback.  ...  The proposed system combines the kernel biased discriminant analysis (KBDA) based low-level learning and semantic log file (SLF) based high-level learning to achieve high retrieval accuracy after the first  ...  The feature vector model based learning is to bring the feature vectors of similar images close to each other by a weighting scheme or a transformation technique.  ... 
doi:10.1109/icassp.2010.5495405 dblp:conf/icassp/FechserCQ10 fatcat:6i7oqxvhojdklnvlaq2hd4f6xy

A Feature Vector Approach for Inter-Query Learning for Content-Based Image Retrieval

Kien-Ping Chung, Chun Che Fung
2007 Journal of Advanced Computational Intelligence and Intelligent Informatics  
Use of relevance feedback (RF) in the feature vector model has been one of the most widely used approaches to fine tuning queries for content-based image retrieval (CBIR).  ...  Using the feature vector model, this avoids the need to "memorize" actual retrieval relationships between actual image indexes and the previous queries.  ...  In the feature vector model approach, images retrieved from a query session are captured as a clustered group and information on retrieved images is stored in the "user log".  ... 
doi:10.20965/jaciii.2007.p0289 fatcat:uerj5mrvyne33fdqu53tmo5auq
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