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Soft Computing

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20.07.2018 | Focus

Sensitivity analysis for image represented by fuzzy function

verfasst von: Petr Hurtik, Nicolás Madrid, Martin Dyba

Erschienen in: Soft Computing | Ausgabe 6/2019

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Abstract

The standard image representation can be considered as obsolete in image processing area since it was designed mainly to visualize images and not to support image processing algorithms. For that reason, seeking alternative image representations becomes an important issue. This paper focuses on images represented by means of fuzzy functions (so-called fuzzy images) and investigates its sensibility under arbitrary distortions. Then, it shows that this fuzzy representation is less sensitive to distortions than the raster image representation. Finally, it also shows the impact on a practical image processing task, where the fuzzy representation has achieved significantly better results.

Vorheriger Artikel Hyperspectral imaging using notions from type-2 fuzzy sets

Nächster Artikel A new edge detection method based on global evaluation using fuzzy clustering

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imagecompression.info/test_images.

Achanta R, Shaji A, Smith K, Lucchi A, Fua P, Süsstrunk S (2012) Slic superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274–2282CrossRef

Arbelaez P, Maire M, Fowlkes C, Malik J (2011) Contour detection and hierarchical image segmentation. IEEE Trans Pattern Anal Mach Intell 33(5):898–916. https://doi.org/10.1109/TPAMI.2010.161 CrossRef

Ballard DH (1981) Generalizing the hough transform to detect arbitrary shapes. Pattern Recogn 13(2):111–122MATHCrossRef

Bradski GR, Davis JW (2002) Motion segmentation and pose recognition with motion history gradients. Mach Vis Appl 13(3):174–184CrossRef

Burger W, Burge MJ (2016) Digital image processing: an algorithmic introduction using Java. Springer, BerlinCrossRef

Canny J (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 6:679–698CrossRef

Chen S-M, Yeh M-S, Hsiao P-Y (1995) A comparison of similarity measures of fuzzy values. Fuzzy Sets Syst 72(1):79–89MathSciNetCrossRef

Cheng C-H (1998) A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets Syst 95(3):307–317MathSciNetMATHCrossRef

Freed L, Ishida S (1995) History of computers. Ziff-Davis Publishing Co., New York

Henderson JM, Brockmole JR, Castelhano MS, Mack M (2007) Visual saliency does not account for eye movements during visual search in real-world scenes. In: Eye movements. Elsevier, pp 537–562

Hoover A, Jean-Baptiste G, Jiang X, Flynn PJ, Bunke H, Goldgof DB, Bowyer K, Eggert DW, Fitzgibbon A, Fisher RB (1996) An experimental comparison of range image segmentation algorithms. IEEE Trans Pattern Anal Mach Intell 18(7):673–689CrossRef

Hurtik P, Madrid N (2015) Bilinear interpolation over fuzzified images: enlargement. In: The 2015 IEEE international conference on fuzzy systems (FUZZ-IEEE 2015)

Hurtik P, Vajgl M, Madrid N (2016) Enhancement of night movies using fuzzy representation of images. In: Fuzzy systems (FUZZ-IEEE), 2016 IEEE international conference on, IEEE. pp 1349–1354

Itti L, Koch C (2000) A saliency-based search mechanism for overt and covert shifts of visual attention. Vis Res 40(10):1489–1506CrossRef

Itti L, Koch C (2001) Feature combination strategies for saliency-based visual attention systems. J Electron Imaging 10(1):161–169CrossRef

Jain AK, Vailaya A (1996) Image retrieval using color and shape. Pattern Recogn 29(8):1233–1244CrossRef

Jain R, Kasturi R, Schunck B G (1995) Machine vision, vol 5. McGraw-Hill, New York

Lewis JP (1995) Fast normalized cross-correlation. Vis Interface 10:120–123

Lopez-Molina C, Madrid N (2017) Non-linear scale-space based on fuzzy sharpening. In: Fuzzy systems association and 9th international conference on soft computing and intelligent systems (IFSA-SCIS), 2017 Joint 17th world congress of international, IEEE, 2017, pp 1–6

Madrid N, Hurtik P (2016) Lane departure warning for mobile devices based on a fuzzy representation of images. Fuzzy Sets Syst 291:144–159MathSciNetCrossRef

Murray J D, VanRyper W (1996) Encyclopedia of graphics file formats, 2nd edn. O’Reilly, Sebastopol

Novák V, Perfilieva I, Mockor J (2012) Mathematical principles of fuzzy logic, vol 517. Springer, BerlinMATH

Rowley HA, Baluja S, Kanade T (1998) Rotation invariant neural network-based face detection. In: Computer vision and pattern recognition, 1998. Proceedings. 1998 IEEE computer society conference on, IEEE, 1998, pp 38–44

Seaborn M, Hepplewhite L, Stonham J (2005) Fuzzy colour category map for the measurement of colour similarity and dissimilarity. Pattern Recogn 38(2):165–177MATHCrossRef

Tran L, Duckstein L (2002) Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy Sets Syst 130(3):331–341MathSciNetMATHCrossRef

Tsai D-M, Lin C-T (2003) Fast normalized cross correlation for defect detection. Pattern Recogn Lett 24(15):2625–2631CrossRef

Viola P, Jones MJ (2004) Robust real-time face detection. Int J Comput Vis 57(2):137–154CrossRef

Voxman W (1998) Some remarks on distances between fuzzy numbers. Fuzzy Sets Syst 100(1–3):353–365MathSciNetMATHCrossRef

Weeks AR (1996) Fundamentals of electronic image processing. SPIE Optical Engineering Press, BellinghamMATHCrossRef

Titel: Sensitivity analysis for image represented by fuzzy function
verfasst von: Petr Hurtik
Nicolás Madrid
Martin Dyba
Publikationsdatum: 20.07.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 6/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-3402-8

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