Abstract
Images are described by various forms of feature descriptors. Especially local invariant features have gained a wide popularity Lowe (Int J Comput Vis 60:91–110, 2004 [17]), Matas et al. (Image Vis Comput 22:761–767, 2004 [18]), Mikolajczyk et al. (Int J Comput Vis 60:63–86, 2004 [20]), Nister Stewenius (Scalable recognition with a vocabulary tree, pp. 2161–2168, 2006 [25]) and Sivic and Zisserman (Video google: a text retrieval approach to object matching in videos, pp. 1470–1477, 2003 [35]).
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (surf). Comput. Vis. Image Underst. 110(3), 346–359 (2008)
Bayer, R., McCreight, E.M.: Organization and maintenance of large ordered indexes. Acta Informatica 1(3), 173–189 (1972). https://doi.org/10.1007/BF00288683
Bosch, A., Zisserman, A., Munoz, X.: Representing shape with a spatial pyramid kernel. In: Proceedings of the 6th ACM International Conference on Image and Video Retrieval, pp. 401–408. ACM (2007)
Bradski, G.: The opencv library. Dr. Dobbs J. 25(11), 120–126 (2000)
Buckland, M., Gey, F.: The relationship between recall and precision. J. Am. Soc. Inf. Sci. 45(1), 12 (1994)
Datar, M., Immorlica, N., Indyk, P., Mirrokni, V.S.: Locality-sensitive hashing scheme based on p-stable distributions. In: Proceedings of the Twentieth Annual Symposium on Computational Geometry, SCG 2004, pp. 253–262. ACM, New York, NY, USA (2004)
Edelkamp, S., Schroedl, S.: Heuristic Search: Theory and Applications. Elsevier (2011)
Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The pascal visual object classes (voc) challenge. Int. J. Comput. Vis. 88(2), 303–338 (2010)
Grauman, K., Darrell, T.: Efficient image matching with distributions of local invariant features. In: Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, vol. 2, pp. 627–634 vol. 2 (2005). https://doi.org/10.1109/CVPR.2005.138
Grycuk, R., Gabryel, M., Scherer, M., Voloshynovskiy, S.: Image descriptor based on edge detection and crawler algorithm. In: International Conference on Artificial Intelligence and Soft Computing, pp. 647–659. Springer International Publishing (2016)
Grycuk, R., Gabryel, M., Scherer, R., Voloshynovskiy, S.: Multi-layer architecture for storing visual data based on WCF and microsoft sql server database. In: Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science, vol. 9119, pp. 715–726. Springer International Publishing (2015)
Grycuk, R., Gabryel, M., Scherer, R., Voloshynovskiy, S.: Multi-layer architecture for storing visual data based on WCF and microsoft sql server database. In: International Conference on Artificial Intelligence and Soft Computing, pp. 715–726. Springer International Publishing (2015)
Hamzah, R.A., Rahim, R.A., Noh, Z.M.: Sum of absolute differences algorithm in stereo correspondence problem for stereo matching in computer vision application. In: 2010 3rd International Conference on Computer Science and Information Technology, vol. 1, pp. 652–657 (2010). https://doi.org/10.1109/ICCSIT.2010.5565062
Korytkowski, M.: Novel visual information indexing in relational databases. Integr. Comput. Aided Eng. 24(2), 119–128 (2017)
Korytkowski, M., Rutkowski, L., Scherer, R.: Fast image classification by boosting fuzzy classifiers. Information Sciences 327, 175–182 (2016). https://doi.org/10.1016/j.ins.2015.08.030. URL http://www.sciencedirect.com/science/article/pii/S0020025515006180
Lazebnik, S., Schmid, C., Ponce, J.: Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2169–2178. IEEE (2006)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)
Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide-baseline stereo from maximally stable extremal regions. Image Vis. Comput. 22(10), 761–767 (2004). British Machine Vision Computing 2002
Meskaldji, K., Boucherkha, S., Chikhi, S.: Color quantization and its impact on color histogram based image retrieval accuracy. In: Networked Digital Technologies, 2009. NDT 2009. First International Conference on, pp. 515–517 (2009). https://doi.org/10.1109/NDT.2009.5272135
Mikolajczyk, K., Schmid, C.: Scale and affine invariant interest point detectors. Int. J. Comput. Vis. 60(1), 63–86 (2004)
Najgebauer, P., Grycuk, R., Scherer, R.: Fast two-level image indexing based on local interest points. In: 2018 23rd International Conference on Methods Models in Automation Robotics (MMAR), pp. 613–617 (2018). https://doi.org/10.1109/MMAR.2018.8485831
Najgebauer, P., Korytkowski, M., Barranco, C.D., Scherer, R.: Artificial Intelligence and Soft Computing: 15th International Conference, ICAISC 2016, Zakopane, Poland, June 12–16, 2016, Proceedings, Part II, chap. Novel Image Descriptor Based on Color Spatial Distribution, pp. 712–722. Springer International Publishing, Cham (2016)
Najgebauer, P., Nowak, T., Romanowski, J., Gabryel, M., Korytkowski, M., Scherer, R.: Content-based image retrieval by dictionary of local feature descriptors. In: 2014 International Joint Conference on Neural Networks, IJCNN 2014, Beijing, China, July 6–11, 2014, pp. 512–517 (2014)
Najgebauer, P., Rygal, J., Nowak, T., Romanowski, J., Rutkowski, L., Voloshynovskiy, S., Scherer, R.: Fast dictionary matching for content-based image retrieval. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science, vol. 9119, pp. 747–756. Springer International Publishing (2015)
Nister, D., Stewenius, H.: Scalable recognition with a vocabulary tree. In: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2, CVPR 2006, pp. 2161–2168. IEEE Computer Society, Washington, DC, USA (2006)
Nowak, T., Najgebauer, P., Romanowski, J., Gabryel, M., Korytkowski, M., Scherer, R., Kostadinov, D.: Spatial keypoint representation for visual object retrieval. In: Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science, vol. 8468, pp. 639–650. Springer International Publishing (2014)
Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.: Object retrieval with large vocabularies and fast spatial matching. In: Computer Vision and Pattern Recognition, 2007. CVPR 2007. IEEE Conference on, pp. 1–8 (2007)
Richardson, I.E.: H. 264 and MPEG-4 Video Compression: Video Coding for Next-generation Multimedia. Wiley (2004)
Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: Orb: An efficient alternative to sift or surf. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 2564–2571 (2011). https://doi.org/10.1109/ICCV.2011.6126544
Rutkowski, L.: Flexible Neuro-Fuzzy Systems. Kluwer Academic Publishers (2004)
Rutkowski, L.: Computational Intelligence Methods and Techniques. Springer, Berlin, Heidelberg (2008)
Schapire, R.E.: A brief introduction to boosting. In: Proceedings of the 16th International Joint Conference on Artificial Intelligence - Volume 2, IJCAI 1999, pp. 1401–1406. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (1999)
Scherer, R.: Designing boosting ensemble of relational fuzzy systems. Int. J. Neural Syst. 20(5), 381388 (2010). http://www.worldscinet.com/ijns/20/2005/S0129065710002528.html
Scherer, R.: Multiple Fuzzy Classification Systems. Springer Publishing Company, Incorporated (2014)
Sivic, J., Zisserman, A.: Video google: a text retrieval approach to object matching in videos. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, 2003. vol. 2, pp. 1470–1477 (2003)
Sopyla, K., Drozda, P., Górecki, P.: Svm with cuda accelerated kernels for big sparse problems. In: ICAISC (1), Lecture Notes in Computer Science, vol. 7267, pp. 439–447. Springer (2012)
Tao, D.: The corel database for content based image retrieval (2009)
Tao, D., Li, X., Maybank, S.J.: Negative samples analysis in relevance feedback. IEEE Trans. Knowl. Data Eng. 19(4), 568–580 (2007)
Tao, D., Tang, X., Li, X., Wu, X.: Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 28(7), 1088–1099 (2006)
Tieu, K., Viola, P.: Boosting image retrieval. Int. J. Comput. Vis. 56(1–2), 17–36 (2004)
Ting, K.M.: Precision and recall. In: Encyclopedia of Machine Learning, pp. 781–781. Springer (2011)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001, vol. 1, pp. I–511–I–518 (2001)
Voloshynovskiy, S., Diephuis, M., Kostadinov, D., Farhadzadeh, F., Holotyak, T.: On accuracy, robustness, and security of bag-of-word search systems. In: IS&T/SPIE Electronic Imaging, pp. 902, 807–902,807. International Society for Optics and Photonics (2014)
Yang, J., Yu, K., Gong, Y., Huang, T.: Linear spatial pyramid matching using sparse coding for image classification. In: IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009, pp. 1794–1801. IEEE (2009)
Zhang, J., Marszalek, M., Lazebnik, S., Schmid, C.: Local features and kernels for classification of texture and object categories: a comprehensive study. In: Conference on Computer Vision and Pattern Recognition Workshop, 2006. CVPRW 2006, pp. 13–13 (2006). https://doi.org/10.1109/CVPRW.2006.121
Zhang, W., Yu, B., Zelinsky, G., Samaras, D.: Object class recognition using multiple layer boosting with heterogeneous features. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. CVPR 2005, vol. 2, pp. 323–330 vol. 2 (2005). https://doi.org/10.1109/CVPR.2005.251
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Scherer, R. (2020). Image Indexing Techniques. In: Computer Vision Methods for Fast Image Classification and Retrieval. Studies in Computational Intelligence, vol 821. Springer, Cham. https://doi.org/10.1007/978-3-030-12195-2_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-12195-2_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-12194-5
Online ISBN: 978-3-030-12195-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)