Use of Low Level Features for Content Based Image Retrieval: Survey

Survey paper reviews the fundamental theories of Content Based Image Retrieval algorithms and development in this field. These algorithms retrieve the digital images from large image database. Image is retrieved from the low level visual content features of query image that is color, texture, shape and spatial location. First we review the visual content description of image and then the fundamental schemes for content based image retrieval are discussed. We also address the comparison of query image and target image of large data base with the indexing scheme to retrieve the image. Relevance feedback in CBIR system is a dominant technique for the retrieval of image which is derived from user’s feedback iteration process. Lastly we discuss the evaluation and semantic gap. In the concluding section we mention our views on role of similarity function with learning and interaction, the problem of evaluation and semantic gap as well as future research directions.

[1]  James Lee Hafner,et al.  Efficient Color Histogram Indexing for Quadratic Form Distance Functions , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Simone Santini,et al.  Similarity Measures , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Le Gruenwald,et al.  Tree-Based Indexes for Image Data , 1998, J. Vis. Commun. Image Represent..

[4]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Wesley E. Snyder,et al.  Application of Affine-Invariant Fourier Descriptors to Recognition of 3-D Objects , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Jianying Hu,et al.  Matching and retrieval based on the vocabulary and grammar of color patterns , 2000, IEEE Trans. Image Process..

[7]  Ying Liu,et al.  A survey of content-based image retrieval with high-level semantics , 2007, Pattern Recognit..

[8]  L. da F. Costa,et al.  An entropy-based approach to automatic image segmentation of satellite images , 2009, 0911.1759.

[9]  Nicu Sebe,et al.  Visual websearching using iconic queries , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[10]  Subrata Rakshit,et al.  Feature Selection in Example-Based Image Retrieval Systems , 2002, ICVGIP.

[11]  Hans-Peter Kriegel,et al.  The R*-tree: an efficient and robust access method for points and rectangles , 1990, SIGMOD '90.

[12]  Jesse S. Jin,et al.  Dimension reduction of texture features for image retrieval using hybrid associative neural networks , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[13]  Carla E. Brodley,et al.  Local versus global features for content-based image retrieval , 1998, Proceedings. IEEE Workshop on Content-Based Access of Image and Video Libraries (Cat. No.98EX173).

[14]  Thomas S. Huang,et al.  Image retrieval with relevance feedback: from heuristic weight adjustment to optimal learning methods , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[15]  Jing Huang,et al.  Color-Spatial Image Indexing and Applications , 1998 .

[16]  Nikolaos D. Doulamis,et al.  Performance evaluation of Euclidean/correlation-based relevance feedback algorithms in content-based image retrieval systems , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[17]  Chahab Nastar,et al.  Relevance feedback and category search in image databases , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[18]  Sunil Arya,et al.  An optimal algorithm for approximate nearest neighbor searching fixed dimensions , 1998, JACM.

[19]  Gultekin Özsoyoglu,et al.  A framework for feature-based indexing for spatial databases , 1994, Seventh International Working Conference on Scientific and Statistical Database Management.

[20]  Tat-Seng Chua,et al.  An integrated color-spatial approach to content-based image retrieval , 1995, MULTIMEDIA '95.

[21]  F. Guo,et al.  Measuring image similarity using the geometrical distribution of image contents , 1998, ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344).

[22]  Rohini K. Srihari,et al.  Spatial color histograms for content-based image retrieval , 1999, Proceedings 11th International Conference on Tools with Artificial Intelligence.

[23]  Robert M. Haralick,et al.  A weighted distance approach to relevance feedback , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[24]  Farzin Mokhtarian,et al.  Silhouette-Based Isolated Object Recognition through Curvature Scale Space , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Isma Irum,et al.  Content Based Image Retrieval by Shape , Color and Relevance Feedback , 2013 .

[26]  Yihong Gong,et al.  An image database system with content capturing and fast image indexing abilities , 1994, 1994 Proceedings of IEEE International Conference on Multimedia Computing and Systems.

[27]  Thomas S. Huang,et al.  Content-based image retrieval with relevance feedback in MARS , 1997, Proceedings of International Conference on Image Processing.

[28]  Dragutin Petkovic,et al.  Content-based representation and retrieval of visual media: A state-of-the-art review , 1996, Multimedia Tools and Applications.

[29]  Raj Jain,et al.  Algorithms and strategies for similarity retrieval , 1996 .

[30]  Esther M. Arkin,et al.  An efficiently computable metric for comparing polygonal shapes , 1991, SODA '90.

[31]  Remco C. Veltkamp,et al.  A survey of content based 3D shape retrieval methods , 2004, Proceedings Shape Modeling Applications, 2004..

[32]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[33]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[34]  Thomas S. Huang,et al.  Relevance feedback: a power tool for interactive content-based image retrieval , 1998, IEEE Trans. Circuits Syst. Video Technol..

[35]  Z. Meral Özsoyoglu,et al.  Distance-based indexing for high-dimensional metric spaces , 1997, SIGMOD '97.

[36]  J. T. Robinson,et al.  The K-D-B-tree: a search structure for large multidimensional dynamic indexes , 1981, SIGMOD '81.

[37]  Anil K. Jain,et al.  Image classification for content-based indexing , 2001, IEEE Trans. Image Process..

[38]  Dragutin Petkovic,et al.  Query by Image and Video Content: The QBIC System , 1995, Computer.

[39]  Stephen M. Smith,et al.  SUSAN—A New Approach to Low Level Image Processing , 1997, International Journal of Computer Vision.

[40]  Matti Pietikäinen,et al.  An Experimental Comparison of Autoregressive and Fourier-Based Descriptors in 2D Shape Classification , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[41]  Shi-Kuo Chang,et al.  Iconic Indexing by 2-D Strings , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[42]  Ramin Zabih,et al.  Comparing images using joint histograms , 1999, Multimedia Systems.

[43]  Qi Tian,et al.  Incorporate support vector machines to content-based image retrieval with relevance feedback , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[44]  Peter N. Yianilos,et al.  Data structures and algorithms for nearest neighbor search in general metric spaces , 1993, SODA '93.

[45]  Pavel Zezula,et al.  M-tree: An Efficient Access Method for Similarity Search in Metric Spaces , 1997, VLDB.

[46]  B. S. Manjunath,et al.  NeTra: A toolbox for navigating large image databases , 1997, Multimedia Systems.

[47]  Hideyuki Tamura,et al.  Textural Features Corresponding to Visual Perception , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[48]  Wei-Yun Yau,et al.  Learning in content based image retrieval - a brief review , 2007, 2007 6th International Conference on Information, Communications & Signal Processing.

[49]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..

[50]  Benjamin B. Kimia,et al.  Symmetry-Based Indexing of Image Databases , 1998, J. Vis. Commun. Image Represent..

[51]  Andre Zaccarin,et al.  Multiscale autoregressive image representation for texture segmentation , 1997, Electronic Imaging.

[52]  Alberto Del Bimbo,et al.  Visual Image Retrieval by Elastic Matching of User Sketches , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[53]  B. S. Adiga,et al.  A Universal Model for Content-Based Image Retrieval , 2008 .

[54]  C. V. Jawahar,et al.  Analysis of Relevance Feedback in Content Based Image Retrieval , 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.

[55]  Arnold W. M. Smeulders,et al.  PicToSeek: combining color and shape invariant features for image retrieval , 2000, IEEE Trans. Image Process..

[56]  D. Ashlock,et al.  Texture synthesis with tandem genetic algorithms using nonparametric partially ordered Markov models , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[57]  Shih-Fu Chang,et al.  Integrated spatial and feature image query , 1999, Multimedia Systems.

[58]  Wai Lok Woo,et al.  A review of content-based image retrieval , 2010, 2010 7th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP 2010).

[59]  Suh-Yin Lee,et al.  2D C-string: A new spatial knowledge representation for image database systems , 1990, Pattern Recognit..

[60]  Robert M. Haralick,et al.  Graph-theoretic clustering for image grouping and retrieval , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[61]  Shi-Kuo Chang,et al.  Image Information Systems: Where Do We Go From Here? , 1992, IEEE Trans. Knowl. Data Eng..

[62]  Rajiv Mehrotra,et al.  Shape-similarity-based retrieval in image database systems , 1992, Electronic Imaging.

[63]  Alireza Khotanzad,et al.  Invariant Image Recognition by Zernike Moments , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[64]  Ramin Zabih,et al.  Histogram refinement for content-based image retrieval , 1996, Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96.

[65]  Aura Conci,et al.  Comparing the influence of color spaces and metrics in content-based image retrieval , 1998, Proceedings SIBGRAPI'98. International Symposium on Computer Graphics, Image Processing, and Vision (Cat. No.98EX237).

[66]  Serge J. Belongie,et al.  Region-based image querying , 1997, 1997 Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries.

[67]  Hyoung-Joo Kim,et al.  A fast content-based indexing and retrieval technique by the shape information in large image database , 2001, J. Syst. Softw..

[68]  Jing Xin,et al.  Relevance Feedback for Content-Based Image Retrieval Using Bayesian Network , 2004, VIP.