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Artificial Intelligence Review

Erschienen in:

02.08.2019

The dissimilarity approach: a review

verfasst von: Yandre M. G. Costa, Diego Bertolini, Alceu S. Britto Jr., George D. C. Cavalcanti, Luiz E. S. Oliveira

Erschienen in: Artificial Intelligence Review | Ausgabe 4/2020

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Abstract

Dissimilarity representation is a very interesting alternative for the traditional feature space representation when addressing large multi-class problems or even problems with a small number of training samples. This paper describes the existing possibilities in terms of dissimilarity representation through some comprehensive examples. The justification for using such a problem representation strategy is discussed, followed by a complete review of the state-of-art and a critical analysis in which the original purpose of the dissimilarity representation and its perspectives are discussed. Dissimilarity space derived from automatically learned features and the possibility of transiting from one space to another when performing the tasks of the classification process are good examples of promising research directions in this field.

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Bertolini D, Oliveira LS, Justino E, Sabourin R (2010) Reducing forgeries in writer-independent off-line signature verification through ensemble of classifiers. Pattern Recognit 43(1):387–396CrossRef

Bertolini D, Oliveira LS, Justino E, Sabourin R (2013) Texture-based descriptors for writer identification and verification. Expert Syst Appl 40(6):2069–2080CrossRef

Bertolini D, Oliveira LS, Sabourin R (2015) Improving writer identification through writer selection. In: Iberoamerican Congress on pattern recognition. Springer, pp 168–175

Bertolini D, Oliveira LS, Sabourin R (2016) Multi-script writer identification using dissimilarity. In: 2016 23rd International conference on pattern recognition (ICPR). IEEE, pp 3025–3030

Bouibed ML, Hassiba N, Chibani Y (2018) Evaluation of gradient descriptors and dissimilarity learning for writer retrieval. In: 2018 Eighth international conference on information science and technology (ICIST), pp 252–256. https://doi.org/10.1109/ICIST.2018.8426179

Bunke H, Riesen K (2008) Graph classification based on dissimilarity space embedding. In: Joint IAPR international workshops on statistical techniques in pattern recognition (SPR) and structural and syntactic pattern recognition (SSPR). Springer, pp 996–1007

Cha S-H (2001) Use of distance measures in handwriting analysis. PhD thesis, Buffalo, AAI3010803

Cha S-H, Srihari SN (2000a) Writer identification: statistical analysis and dichotomizer. In: Ferri FJ, Iñesta JM, Amin A, Pudil P (eds) Advances in pattern recognition. Springer, Berlin, pp 123–132. ISBN 978-3-540-44522-7

Cha S-H, Srihari SN (2000b) Writer identification: statistical analysis and dichotomizer. In: Joint IAPR international workshops on statistical techniques in pattern recognition (SPR) and structural and syntactic pattern recognition (SSPR). Springer, pp 123–132

Duin RPW, Pękalska E (2012) The dissimilarity space: bridging structural and statistical pattern recognition. Pattern Recognit Lett 33(7):826–832CrossRef

Duin RPW, Loog M, Pękalska E, Tax DMJ (2010) Feature-based dissimilarity space classification. In: Recognizing patterns in signals, speech, images and videos. Springer, pp 46–55

Eskander GS, Sabourin R, Granger E (2013) Eric hybrid writer-independent–writer-dependent offline signature verification system. IET Biom 2:169–181(12). ISSN 2047-4938

Garcia S, Derrac J, Cano JR, Herrera F (2011) Prototype selection for nearest neighbor classification: taxonomy and empirical study. IEEE Trans Pattern Anal Mach Intell 3:417–435

Hanusiak RK, Oliveira LS, Justino E, Sabourin R (2012) Writer verification using texture-based features. Int J Doc Anal Recognit (IJDAR) 15(3):213–226. ISSN 1433-2825. https://doi.org/10.1007/s10032-011-0166-4

Haralick RM, Shanmugam K, Dinstein IH (1973) Textural features for image classification. IEEE Trans Syst Man Cybern 3(6):610–621CrossRef

Livi L, Rizzi A, Sadeghian A (2014) Optimized dissimilarity space embedding for labeled graphs. Inf Sci 266:47–64MathSciNetCrossRef

Martins JG, Oliveira LS, Britto AS, Sabourin R (2015) Forest species recognition based on dynamic classifier selection and dissimilarity feature vector representation. Mach Vis Appl 26(2–3):279–293CrossRef

Nguyen GP, Worring M, Smeulders AWM (2006) Similarity learning via dissimilarity space in CBIR. In: Proceedings of the 8th ACM international workshop on multimedia information retrieval. ACM, pp 107–116

Okawa M, Yoshida K (2013) User generic model for writer verification using multiband image scanner. In: 2013 IEEE International conference on technologies for homeland security (HST). IEEE, pp 375–380

Oliveira LS, Justino E, Sabourin R (2007) Off-line signature verification using writer-independent approach. In: 2007 International joint conference on neural networks, pp 2539–2544. https://doi.org/10.1109/IJCNN.2007.4371358

Pavelec D, Justino E, Batista LV, Oliveira LS (2008) Author identification using writer-dependent and writer-independent strategies. In: Proceedings of the 2008 ACM symposium on applied computing, SAC ’08. ACM, New York, pp 414–418. ISBN 978-1-59593-753-7. https://doi.org/10.1145/1363686.1363788

Pčkalska E, Duin RPW (2005) The dissimilarity representation for pattern recognition: foundations and applications. World Scientific, SingaporeCrossRef

Pękalska EM (2005) Dissimilarity representations in pattern recognition. concepts, theory and applications. Thesis. http://rduin.nl/papers/pekalska_thesis.pdf

Pękalska E, Duin RPW (2006) Dissimilarity-based classification for vectorial representations. In: 18th International conference on pattern recognition, 2006. ICPR 2006, vol 3. IEEE, pp 137–140

Pękalska E, Paclik P, Duin RPW (2001) A generalized kernel approach to dissimilarity-based classification. J Mach Learn Res 2(Dec):175–211MathSciNetMATH

Pękalska E, Paclik P, Duin RPW (2002) Dissimilarity representations allow for building good classifiers. Pattern Recognit Lett 23(8):943–956. ISSN 0167-8655. https://doi.org/10.1016/S0167-8655(02)00024-7

Pękalska E, Duin RPW, Paclík P (2006) Prototype selection for dissimilarity-based classifiers. Pattern Recognit 39(2):189–208CrossRef

Pinheiro RHW, Cavalcanti GDC, Tsang IR (2017) Combining dissimilarity spaces for text categorization. Inf Sci 406–407:87–101. ISSN 0020-0255. https://doi.org/10.1016/j.ins.2017.04.025

Pinheiro RHW, Cavalcanti GDC, Tsang IR (2019) Combining binary classifiers in different dichotomy spaces for text categorization. Appl Soft Comput 76:564–574. ISSN 1568-4946. https://doi.org/10.1016/j.asoc.2018.12.023

Riesen K, Bunke H (2009) Reducing the dimensionality of dissimilarity space embedding graph kernels. Eng Appl Artif Intell 22(1):48–56CrossRef

Rivard D, Granger E, Sabourin R (2013) Multi-feature extraction and selection in writer-independent off-line signature verification. Int J Doc Anal Recognit (IJDAR) 16(1):83–103. ISSN 1433-2825. https://doi.org/10.1007/s10032-011-0180-6

Santini S, Jain R (1999) Similarity measures. IEEE Trans Pattern Anal Mach Intell 21(9):871–883CrossRef

Souza VLF, Oliveira ALI, Sabourin R (2018) A writer-independent approach for offline signature verification using deep convolutional neural networks features. arXiv preprint arXiv:1807.10755,

Swanepoel JP, Coetzer J (2012) Writer-specific dissimilarity normalisation for improved writer-independent off-line signature verification. In: 2012 International conference on frontiers in handwriting recognition, pp 393–398. https://doi.org/10.1109/ICFHR.2012.290

Theodorakopoulos I, Economou G, Fotopoulos S (2013) Collaborative sparse representation in dissimilarity space for classification of visual information. In: Bebis G, Boyle R, Parvin B, Koracin D, Li B, Porikli F, Zordan V, Klosowski J, Coquillart S, Luo X, Chen M, Gotz D (eds) Advances in visual computing. Springer, Berlin, pp 496–506. ISBN 978-3-642-41914-0

Theodorakopoulos I, Kastaniotis D, Economou G, Fotopoulos S (2014a) Hep-2 cells classification via sparse representation of textural features fused into dissimilarity space. Pattern Recognit 47(7):2367–2378CrossRef

Theodorakopoulos I, Kastaniotis D, Economou G, Fotopoulos S (2014b) Pose-based human action recognition via sparse representation in dissimilarity space. J Vis Commun Image Represent 25(1):12–23CrossRef

Triguero I, Derrac J, Garcia S, Herrera F (2012) A taxonomy and experimental study on prototype generation for nearest neighbor classification. IEEE Trans Syst Man Cybern Part C (Appl Rev) 42(1):86–100CrossRef

Van Gemert JC, Geusebroek J, Veenman CJ, Snoek CGM, Smeulders AWM (2006) Robust scene categorization by learning image statistics in context. In: Conference on computer vision and pattern recognition workshop, 2006. IEEE, pp 105–105

Zottesso RHD, Costa YMG, Bertolini D, Oliveira LS (2018) Bird species identification using spectrogram and dissimilarity approach. Ecol Inform 48:187–197. ISSN 1574-9541. https://doi.org/10.1016/j.ecoinf.2018.08.007(in press)

Titel: The dissimilarity approach: a review
verfasst von: Yandre M. G. Costa
Diego Bertolini
Alceu S. Britto Jr.
George D. C. Cavalcanti
Luiz E. S. Oliveira
Publikationsdatum: 02.08.2019
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 4/2020
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-019-09746-z

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