Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Introduction Read chapter Read first chapter

2012 | OriginalPaper | Chapter

4. Feature Extraction

Author : Prof. A. Ardeshir Goshtasby

Published in: Image Registration

Publisher: Springer London

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This chapter discusses various image features used in image matching. The features measure statistical, geometric, algebraic, spatial, differential, color, fractal, information-theoretic, and other image properties. Overall, 122 image features are described and 47 of them are compared for accuracy and speed, as well as for sensitivity to noise, blurring, and intensity and geometric changes. In addition, dependency of the features on template or image size are examined and compared.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Point Detectors
next chapter Image Descriptors
Literature
1.
Abo-Zaid, A., Hinton, O., Horne, E.: About moment normalisation and complex moment descriptors. In: Proc. 4th Int’l Conf. Pattern Recognition, pp. 399–407 (1988)
2.
Abu-Mostafa, Y.S., Psaltis, D.: Recognitive aspects of moment invariants. IEEE Trans. Pattern Anal. Mach. Intell. 6(6), 698–706 (1984) CrossRef
3.
Abu-Mostafa, Y.S., Psaltis, D.: Image normalization by complex moments. IEEE Trans. Pattern Anal. Mach. Intell. 7(1), 46–55 (1985) CrossRef
4.
Aburdene, M.F.: On the computation of discrete Legendre polynomial coefficients. Multidimens. Syst. Signal Process. 4, 181–186 (1993) MathSciNetMATHCrossRef
5.
Ahmed, N., Natarajan, T., Rao, K.R.: On image processing and a discrete cosine transform. IEEE Trans. Commun. 23(1), 90–93 (1974) MathSciNetMATHCrossRef
6.
Ando, S.: Image field categorization and edge/corner detection from gradient covariance. IEEE Trans. Pattern Anal. Mach. Intell. 22(2), 179–190 (2000) CrossRef
7.
Andreadis, I., Tsalides, Ph.: Coloured object recognition using invariant spectral features. J. Intell. Robot. Syst. 13, 93–106 (1995) CrossRef
8.
Andrews, H.C.: Computer Techniques in Image Processing. Academic Press, New York (1970)
9.
Andrews, H.C., Patterson, C.L.: Singular value decomposition and digital image processing. In: IEEE Trans. Acoustics, Speech, and Signal Processing, pp. 26–53 (1976)
10.
Andrews, H.C., Patterson, C.L.: Singular value decomposition (SVD) image coding. In: IEEE Trans. Communications, pp. 425–432 (1976)
11.
Bajcsy, R.: Computer description of textured surfaces. In: Proc. 3rd Int’l J. Conf. Artificial Intelligence, pp. 572–579 (1973)
12.
Ballester, C., González, M.: Affine invariant texture segmentation and shape from texture by variational methods. J. Math. Imaging Vis. 9, 141–171 (1998) MATHCrossRef
13.
Barnard, S.T., Thompson, W.B.: Disparity analysis of images. IEEE Trans. Pattern Anal. Mach. Intell. 2(4), 333–340 (1980) CrossRef
14.
Baumberg, A.: Reliable feature matching across widely separated views. In: IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 774–781 (2000)
15.
Beaudet, P.R.: Rotationally invariant image operators. In: Proc. Int’l Conf. Pattern Recognition, pp. 579–583 (1978)
16.
Belkasim, S.O., Ahmadi, M., Shridhar, M.: Efficient algorithm for fast computation of Zernike moments. J. Franklin Inst. 333B(4), 577–581 (1996) MathSciNetMATHCrossRef
17.
Belkasim, S., Hassan, E., Obeidi, T.: Explicit invariance of Vartesian Zernike moments. Pattern Recognit. Lett. 28, 1969–1980 (2007) CrossRef
18.
Benke, K.K., Skinner, D.R., Woodruff, C.J.: Convolution operators as a basis for objective correlates of texture perception. IEEE Trans. Syst. Man Cybern. 18(1), 158–163 (1988) CrossRef
19.
Blostein, D., Ahuja, N.: A multiscale region detector. Comput. Vis. Graph. Image Process. 45, 22–41 (1989) CrossRef
20.
Borgefors, G.: Distance transforms in digital images. Comput. Vis. Graph. Image Process. 34, 344–371 (1986) CrossRef
21.
Bovik, A.C., Clark, M., Geisler, W.S.: Multichannel texture analysis using localized spatial filters. IEEE Trans. Pattern Anal. Mach. Intell. 12(1), 55–73 (1990) CrossRef
22.
Canterakis, N.: 3-D Zernike moments and Zernike affine invariants for 3D image analysis and recognition. In: Proc. 11th Scandinavian Conference on Image Analysis (1999)
23.
Carneiro, G., Jepson, A.D.: Phase-based local features. In: European Conf. Computer Vision, Copenhagen, Denmark, pp. 282–296 (2002)
24.
Carneiro, G., Jepson, A.D.: Multi-scale phase-based local features. In: Proc. Computer Vision and Pattern Recognition, vol. 1, pp. 736–743 (2003)
25.
Chan, Y.-K., Chen, C.-Y.: Image retrieval system based on color-complexity and color-spatial features. J. Syst. Softw. 71, 65–70 (2004) CrossRef
26.
Chang, T., Kuo, C.-C.: Texture analysis and classification with tree-structured wavelet transform. IEEE Trans. Image Process. 2(4), 429–441 (1993) CrossRef
27.
Chen, C.-C., Daponte, J.S., Fox, M.D.: Fractal feature analysis and classification in medical imaging. IEEE Trans. Med. Imaging 8(2), 133–142 (1989) CrossRef
28.
Chen, E.-L., Chung, P.-C., Chen, C.-L., Tsai, H.-M., Chang, C.-I.: An automatic diagnostic system for CT liver image classification. IEEE Trans. Biomed. Eng. 45(6), 783–794 (1998) CrossRef
29.
Chen, D.-R., Chang, R.-F., Chen, C.-J., Ho, M.-F., Huo, S.-J., Chen, S.-T., Hung, S.-J., Moons, W.K.: Classification of breast ultrasound images using fractal feature. J. Clin. Imaging 29, 235–245 (2005) CrossRef
30.
Cheng, Y., Swamisai, R., Umbaugh, S.E., Moss, R.H., Stoecker, W.V., Teegala, S., Srinivasan, S.K.: Skin lesion classification using relative color features. Skin Res. Technol. 14, 53–64 (2008)
31.
Chhabra, A.K., Zhigang, A., Balick, D., Genevieve, C., Loris, K., Sheppard, P., Smith, R., Wittner, B.: High-order statistically derived combinations of geometric features for handprinted character recognition. In: Proc. Second Int’l Conf. Document Analysis and Recognition, pp. 397–401 (1993)
32.
Chui, C.K., Wang, J.-Z.: On compactly supported spline wavelets and a duality principle. Trans. Am. Math. Soc. 330(2), 903–915 (1992) MathSciNetMATHCrossRef
33.
Clementini, E., Di Felice, P.: A model for representing topological relationships between complex geometric features in spatial databases. Inf. Sci. 90, 121–136 (1996) MATHCrossRef
34.
Clementini, E., Di Felice, P., van Oosterom, P.: A small set of formal topological relationships suitable for end-user interaction. Lect. Notes Comput. Sci. 692, 277–295 (1993) CrossRef
35.
Coggins, J.M., Jain, A.K.: A spatial filtering approach to texture analysis. Pattern Recognit. Lett. 3(3), 195–203 (1985) CrossRef
36.
Cohen, P., LeDinh, C.T., Lacasse, V.: Classification of textures by means of two-dimensional orthogonal masks. IEEE Trans. Acoust. Speech Signal Process. 37(1), 125–128 (1989) CrossRef
37.
Collignon, A., Maes, F., Delaere, D., Vandermeulen, D., Suetens, P., Marchal, A.: Automated multi-modality image registration based on information theory. In: Proc. Information Processing in Medicine Conf, pp. 263–274 (1995)
38.
Conners, R.W., Harlow, C.A.: A theoretical comparison of texture algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 2(3), 204–222 (1980) MATHCrossRef
39.
Conover, W.J.: Practical Nonparametric Statistics, 2nd edn., p. 252. Wiley, New York (1980)
40.
Cunha, A.L., Zhou, J., Do, M.N.: The nonsubsampled contourlet transform: Theory, design, and applications. IEEE Trans. Image Process. 15, 3089–3101 (2006) CrossRef
41.
Damon, J., Giblin, P., Haslinger, G.: Local image features resulting from 3-dimensional geometric features, illumination, and movement: I. Int. J. Comput. Vis. 82, 25–47 (2009) MATHCrossRef
42.
Danielsson, P.E.: Euclidean distance mapping. Comput. Graph. Image Process. 14, 227–248 (1980) CrossRef
43.
44.
Daubechies, I.: The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inf. Theory 36, 961–1005 (1990) MathSciNetMATHCrossRef
45.
Daugman, J.G.: Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. J. Opt. Soc. Am. 2, 1160–1169 (1985) CrossRef
46.
Deriche, R., Giraudon, G.: Accurate corner detection: An analytical study. In: Proc. 3rd Int’l Conf. Computer Vision, Osaka, Japan, pp. 66–70 (1990)
47.
Do, M.H., Vetterli, M.: The contourlet transform: An efficient multiresolution image representation. IEEE Trans. Image Process. 14, 2091–2106 (2005) MathSciNetCrossRef
48.
Dondes, P.A., Rosenfeld, A.: Pixel classification based on gray level and local ‘busyness’. IEEE Trans. Pattern Anal. Mach. Intell. 4(1), 79–84 (1982) CrossRef
49.
Dunn, D.F., Higgins, W.E.: Optimal Gabor filters for texture segmentation. IEEE Trans. Image Process. 4(7), 947–964 (1995) CrossRef
50.
Dyer, C.R., Rosenfeld, A.: Fourier texture features: Suppression of aperature effects. IEEE Trans. Syst. Man Cybern. 6, 703–705 (1976) CrossRef
51.
Feng, G., Jiang, J.: JPEG compressed image retrieval via statistical features. Pattern Recognit. 36, 977–985 (2003) CrossRef
52.
Feng, Z., Shang-qian, L., Da-bao, W., Wei, G.: Aircraft recognition in infrared image using wavelet moment invariants. Image Vis. Comput. 27, 313–318 (2009) CrossRef
53.
Fergus, R., Perona, P., Zisserman, A.: Object class recognition by unsupervised scale-invariant learning. In: Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, pp. II-264–II-271 (2003)
54.
Field, D.J.: Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A 4, 2379–2394 (1987) CrossRef
55.
Fischer, S., Šroubek, F., Perrinet, L., Redondo, R., Cristóbal, G.: Self-invertible 2D log-polar wavelets. Int. J. Comput. Vis. 75(2), 231–246 (2007) CrossRef
56.
57.
58.
Förstner, W.: A feature based correspondence algorithm for image matching. Int. Arch. Photogramm. Remote Sens. 26, 150–166 (1986)
59.
Freeman, W.T., Adelson, W.H.: The design and use of steerable filters. IEEE Trans. Pattern Anal. Mach. Intell. 13(9), 891–906 (1991) CrossRef
60.
Funt, B.V., Finlayson, G.D.: Color constant color indexing. IEEE Trans. Pattern Anal. Mach. Intell. 17(5), 522–529 (1995) CrossRef
61.
Gabor, D.: Theory of communication. J. Inst. Electr. Eng. 93(26), 429–457 (1946)
62.
Galloway, M.M.: Texture analysis using gray level run lengths. Comput. Graph. Image Process. 4, 172–179 (1975) CrossRef
63.
Garcia, C., Zikos, G., Tziritas, G.: A wavelet-based framework for face recognition. Image Vis. Comput. 18, 289–297 (2000) CrossRef
64.
Gårding, J., Lindeberg, T.: Direct computation of shape cues using scale-accepted spatial derivative operators. Int. J. Comput. Vis. 17(2), 163–191 (1996) CrossRef
65.
Gong, P., Howarth, P.J.: An assessment of some small window-based spatial features for land-cover classification. In: Int’l Conf. Geoscience and Remote Sensing Symposium, vol. 4, pp. 1668–1670 (1993)
66.
Gonzalez, R.C., Wintz, P.: Digital Image Processing, 2nd edn., pp. 122–125. Addison-Wesley, Reading (1987)
67.
Goshtasby, A.: 2-D and 3-D Image Registration for Medical, Remote Sensing, and Industrial Applications. Wiley, New York (2005)
68.
Goshtasby, A., O’Neill, W.: Surface fitting to scattered data by a sum of Gaussians. Comput. Aided Geom. Des. 10, 143–156 (1993) MathSciNetMATHCrossRef
69.
Goshtasby, A., O’Neill, W.: Curve fitting by a sum of Gaussians. Graph. Models Image Process. 56(4), 281–288 (1994) CrossRef
70.
Hannah, M.J.: Computer matching of areas in stereo images. Ph.D. Dissertation, Stanford University, Department of Computer Science (1974)
71.
Hansen, B.B., Morse, B.S.: Multiscale image registration using scale trace correlation. In: Proc. Computer Vision and Pattern Recognition, pp. 202–208 (1999)
72.
Haralick, R.M.: Statistical and structural approaches to texture. Proc. IEEE 67(5), 786–807 (1979) CrossRef
73.
Haralick, R.M., Shanmugam, K., Dinstein, I.: Texture features for image classification. IEEE Trans. Syst. Man Cybern. 3(6), 610–621 (1973) CrossRef
74.
Harris, C., Stephens, M.: A combined corner and edge detector. In: Proc. 4th Alvey Vision Conf. (AVC88), Univ. Manchester, pp. 147–151 (1988)
75.
Harwood, D., Ojala, T., Pietikäinen, M., Kelman, S., Davis, L.S.: Texture classification by center-symmetric autocorrelation, using Kullback discrimination of distributions. Pattern Recognit. Lett. 16, 1–10 (1995) CrossRef
76.
Hayley, G.M., Manjunath, B.M.: Rotation invariant texture classification using modified Gabor filters. In: Proc. of IEEE Int’l Conf. Image Processing, pp. 262–265 (1995) CrossRef
77.
Heo, Y.S., Lee, M., Lee, S.U.: Robust stereo matching using adaptive normalized cross-correlation. IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 807–822 (2011) MathSciNetCrossRef
78.
Hong, Z.: Algebraic feature extraction of image for recognition. Pattern Recognit. 24, 211–219 (1991) CrossRef
79.
Horikawa, Y.: A feature of 2D and 3D image invariant to similarity transformations based on the bispectrum. Syst. Comput. Jpn. 33(3), 1–10 (2002) CrossRef
80.
Hu, M.K.: Visual pattern recognition by moment invariants. IEEE Trans. Inf. Theory 8, 179–187 (1962) MATH
81.
Jain, A.K., Farrokhnia, F.: Unsupervised texture segmentation using Gabor filters. In: Proc. Int’l Conf. Systems, Man, and Cybernetics, pp. 14–19 (1990)
82.
Jain, A.K., Farrokhnia, F.: Unsupervised texture segmentation using Gabor filters. Pattern Recognit. 24, 1167–1186 (1991) CrossRef
83.
Jain, A., Healey, G.: A multiscale representation including opponent color features for texture recognition. IEEE Trans. Image Process. 7(1), 124–128 (1998) CrossRef
84.
Jernigan, M.E., D’Astous, F.: Entropy-based texture analysis in the spatial frequency domain. IEEE Trans. Pattern Anal. Mach. Intell. 6(2), 237–243 (1984) CrossRef
85.
Jin, L., Tianxu, Z.: Fast algorithm for generation of moment invariants. Pattern Recognit. 37, 1745–1756 (2004) MATHCrossRef
86.
Joanes, D.N., Gill, C.A.: Comparing measures of sample skewness and kurtosis. J. R. Stat. Soc., Ser. D Stat. 47(1), 183–189 (1998) CrossRef
87.
Johansson, B., Borga, M., Knutsson, H.: Learning corner orientation using canonical correlation. In: Proc. SSAB Symposium on Image Analysis, pp. 89–92 (2001)
88.
Johnson, A.E., Hebert, M.: Recognizing objects by matching oriented points. In: Proc. Computer Vision and Pattern Recognition, pp. 684–689 (1997)
89.
Kadir, T., Brady, J.M.: Scale, saliency and image description. Int. J. Comput. Vis. 45(2), 83–105 (2001) MATHCrossRef
90.
Kadyrov, A., Petrou, M.: The trace transform as a tool to invariant feature construction. In: Proc. 14th Int’l Conf. Pattern Recognition, vol. 2, pp. 1037–1039 (1998)
91.
Kadyrov, A., Petrou, M.: The trace transform and its application. IEEE Trans. Pattern Anal. Mach. Intell. 23(8), 811–828 (2001) CrossRef
92.
Kasson, J.K., Plouffe, W.: An analysis of selected computer interchange color spaces. ACM Trans. Graph. 11(4), 373–405 (1992) MATHCrossRef
93.
Khotanzad, A., Hong, Y.H.: Invariant image recognition by Zernike moments. IEEE Trans. Pattern Anal. Mach. Intell. 12(5), 489–497 (1990) CrossRef
94.
Kingsbury, N.G.: Complex wavelets for shift invariant analysis and filtering of signals. J. Appl. Comput. Harmon. Anal. 10(3), 234–253 (2001) MathSciNetMATHCrossRef
95.
Kitchen, L., Rosenfeld, A.: Gray level corner detection. Technical Report #887, Computer Science Center, University of Maryland (1980). Also in Pattern Recogn. Lett. 1, 95–102 (1982)
96.
Koenderink, J.J., van Doorn, A.J.: Representation of local geometry in the visual system. Biol. Cybern. 55, 367–375 (1987) MATHCrossRef
97.
Kovesi, P.: Detection of interest points using symmetry. In: Proc. 3rd Int’l Conf. Computer Vision, pp. 62–65 (1990)
98.
Kyrki, V., Kamarainen, J.-K., Kälviäninen, H.: Simple Gabor feature space for invariant object recognition. Pattern Recognit. Lett. 25, 311–318 (2004) CrossRef
99.
Laws, K.I.: Rapid texture identification. In: Image Processing for Missile Guidance, Proc. SPIE, vol. 238, pp. 376–380 (1980) CrossRef
100.
Lazebnik, S., Schmid, C., Ponce, J.: Sparse texture representation using affine-invariant neighborhoods. In: Proc. Computer Vision and Pattern Recognition, pp. 319–324 (2003)
101.
Lazebnik, S., Schmid, C., Ponce, J.: Semi-local affine parts for object recognition. In: British Machine Vision Conf., vol. 2, pp. 959–968 (2004)
102.
Lazebnik, S., Schmid, C., Ponce, J.: Sparse texture representation using local affine regions. IEEE Trans. Pattern Anal. Mach. Intell. 27(8), 1265–1278 (2005) CrossRef
103.
Le Moigne, J., Zavorin, I., Stone, H.: On the use of wavelets for image registration. In: Le Moigne, J., Netanyahu, N.S., Eastman, R.D. (eds.) Image Registration for Remote Sensing, pp. 240–264. Cambridge University Press, Cambridge (2011) CrossRef
104.
Lee, M.-C., Pun, C.-M.: Rotation and scale invariant wavelet feature for content-based texture retrieval. J. Am. Soc. Inf. Sci. Technol. 54(1), 66–80 (2003) CrossRef
105.
Lee, W.-L., Chen, Y.-C., Hsieh, K.-S.: Ultrasonic liver tissues classification by fractal feature vector on M-band wavelet transform. IEEE Trans. Med. Imaging 22(3), 382–392 (2003) MathSciNetCrossRef
106.
Lee, W.-L., Chen, Y.-C., Chen, Y.-C., Hsieh, K.-S.: Unsupervised segmentation of ultrasonic liver images by multiresolution fractal feature vector. Inf. Sci. 175, 177–199 (2005) CrossRef
107.
Levine, M.D.: Feature extraction: A survey. Proc. IEEE 57(8), 1391–1407 (1969) CrossRef
108.
Li, Y.: Reforming the theory of invariant moments for pattern recognition. Pattern Recognit. 25(7), 723–730 (1992) CrossRef
109.
Liang, K.-C., Jay Kuo, C.-C.: WaveGuide: A joint wavelet-based image representation and description system. IEEE Trans. Image Process. 8(11), 1619–1929 (1999) CrossRef
110.
Liao, S.X., Pawlak, M.: On image analysis by moments. IEEE Trans. Pattern Anal. Mach. Intell. 18(3), 254–266 (1998) CrossRef
111.
Liao, S.X., Pawlak, M.: On the accuracy of Zernike moments for image analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(12), 1358–1364 (1998) CrossRef
112.
Lim, J.S.: The discrete Fourier transform. In: Two-Dimensional Signal and Image Processing, pp. 136–183. Prentice Hall, New York (1990)
113.
Liu, K., Cheng, Y.-Q., Yang, J.-Y.: Algebraic feature extraction for image recognition based on an optimal discriminant criterion. Pattern Recognit. 26(6), 903–911 (1993) CrossRef
114.
Lohmann, A.W., Wirnitzer, B.: Tripple correlations. Proc. IEEE 72(7), 889–901 (1984) CrossRef
115.
Lowe, D.G.: Object recognition from local scale-invariant features. In: Proc. Int’l Conf. Computer Vision, vol. 2, pp. 1150–1157 (1999)
116.
Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004) CrossRef
117.
Loy, G., Zelinsky, A.: A fast radial symmetry transform for detecting points of interest. In: 7th European Conf. Computer Vision, pp. 358–368 (2002)
118.
Lu, T.-C., Chang, C.-C.: Color image retrieval technique based on color features and image bitmap. Inf. Process. Manag. 43, 461–472 (2007) CrossRef
119.
Lundahl, T., Ohley, W.J., Kay, S.M., Siffert, R.: Brownian motion: A maximum likelihood estimator and its application to image texture. IEEE Trans. Med. Imaging 5(3), 152–161 (1986) CrossRef
120.
121.
Mallat, S.G.: A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 11(7), 674–693 (1989) MATHCrossRef
122.
Mallat, S.: A Wavelet Tour of Signal Processing. Academic Press, New York (1998) MATH
123.
Manjunath, B.S., Ma, W.Y.: Texture features for browsing and retrieval of image data. IEEE Trans. Pattern Anal. Mach. Intell. 18(8), 837–842 (1996) CrossRef
124.
Manjunath, B.S., Shekhar, C., Chellappa, R.: A new approach to image feature detection with applications. Pattern Recognit. 29(4), 627–640 (1996) CrossRef
125.
Marabini, R., Carazo, J.M.: On a new computationally fast image invariant based on bispectrum projections. Pattern Recognit. Lett. 17, 956–967 (1996) CrossRef
126.
Masry, E.: Wavelet transform of stochastic processes with stationary increments and its application to fractional Brownian motion. IEEE Trans. Inf. Theory 39, 260–264 (1993) MathSciNetMATHCrossRef
127.
Mikolajczyk, K., Tyetelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Van Gool, L.: A comparison of affine region detectors. Int. J. Comput. Vis. 65(1/2), 43–72 (2005) CrossRef
128.
Mitchell, R., Myer, C.R., Boyne, W.: A max-min measure for image texture analysis. IEEE Trans. Comput. 26, 408–414 (1977) CrossRef
129.
Mohammed, A.-R., Jie, Y.: Practical fast computation of Zernike moments. J. Comput. Sci. Technol. 17(2), 181–188 (2002) MATHCrossRef
130.
Montanari, U.: A method for obtaining skeletons using a quasi-Euclidean distance. J. ACM 15(4), 600–624 (1968) CrossRef
131.
Moravec, H.P.: Towards automatic visual obstacle avoidance. In: Proc. Int’l Joint Conf. Artificial Intelligence, p. 584 (1977)
132.
Moravec, H.P.: Rover visual obstacle avoidance. In: Proc. Int’l Joint Conf. Artificial Intelligence, pp. 785–790 (1981)
133.
Mukundan, R.: Some computational aspects of discrete orthogonal moments. IEEE Trans. Image Process. 13(8), 1055–1059 (2004) MathSciNetCrossRef
134.
135.
Murase, H., Nayar, S.: Visual learning and recognition of 3-D objects from appearance. Int. J. Comput. Vis. 14, 5–24 (1995) CrossRef
136.
Nagel, H.H.: Displacement vectors derived from second order intensity variations in image sequences. Comput. Vis. Graph. Image Process. 21, 85–117 (1983) CrossRef
137.
Novotni, M., Klein, R.: Shape retrieval using 3D Zernike descriptors. Comput. Aided Des. 36, 1047–1062 (2004) CrossRef
138.
Ojala, T., Pietikäinen, M.: Unsupervised texture segmentation using feature distribution. Pattern Recognit. 32, 477–486 (1999) CrossRef
139.
Ojala, T., Pietikäinen, M., Harwood, D.: A comparative study of texture measures with classification based on feature distributions. Pattern Recognit. 29(1), 51–59 (1996) CrossRef
140.
Oppenheim, A.V., Lim, J.S.: The importance of phase in signals. Proc. IEEE 69(5), 529–541 (1981) CrossRef
141.
Oren, M., Papageorgiou, C., Sinha, P., Osuna, E., Poggio, T.: Pedestrian detection using wavelet templates. In: Proc. Computer Vision and Pattern Recognition, pp. 193–199 (1997)
142.
Palm, C., Keysers, D., Lehmann, T., Spitzer, K.: Gabor filtering of complex hue/saturation images for color texture classification. In: Int. Conf. Computer Vision, Atlantic City, NJ, vol. 2, pp. 45–49 (2000)
143.
Papageorgiou, C.P., Oren, M., Poggio, T.: A general framework for object detection. In: 6th Int’l Conf. Computer Vision, pp. 555–562 (1998)
144.
Papakostas, G.A., Boutalis, Y.S., Papaodysseus, C.N., Fragoulis, D.K.: Numerical error analysis in Zernike moments computation. Image Vis. Comput. 24, 960–969 (2006) CrossRef
145.
Papakostas, G.A., Boutalis, Y.S., Karras, D.A., Mertzois, B.G.: A new class of Zernike moments for computer vision applications. Inf. Sci. 177, 1802–2819 (2007) CrossRef
146.
Papakostas, G.A., Karakasis, E.G., Koulouriotis, D.E.: Efficient and accurate computation of geometric moments on gray-scale images. Pattern Recognit. 41, 1895–1904 (2008) MATHCrossRef
147.
Papakostas, G.A., Karakasis, E.G., Koulouriotis, D.E.: Accurate and speedy computation of image Legendre moments for computer vision applications. Image Vis. Comput. 28, 414–423 (2010) CrossRef
148.
Peleg, S., Naor, J., Hartley, R., Avnir, D.: Multiple resolution texture analysis and classification. IEEE Trans. Pattern Anal. Mach. Intell. 6(4), 519–523 (1984) CrossRef
149.
Pentland, A.: Fractal-based description of natural scenes. IEEE Trans. Pattern Anal. Mach. Intell. 6(6), 661–674 (1984) CrossRef
150.
Peterson, K., Ziglar, J., Rybski, P.E.: Fast feature detection and stochastic parameter estimation of road shape using multiple LIDAR. In: Proc. Int’l Conf. Intelligent Robot Systems, pp. 612–619 (2008)
151.
Petrou, M., Kadyrov, A.: Affine invariant features from the trace transform. IEEE Trans. Pattern Anal. Mach. Intell. 26(1), 30–44 (2004) CrossRef
152.
Pratt, W.K., Kane, J., Andrews, H.C.: Hadamard transform image coding. In: Proc. IEEE, pp. 58–70 (1969)
153.
Pratt, W.K., Welch, L.R., Chen, W.H.: Slant transform for image coding. In: Proc. Symp. Application of Walsh Functions, pp. 229–234 (1972)
154.
Pun, C.-M.: Rotation-invariant texture feature for image retrieval. Comput. Vis. Image Underst. 89, 24–43 (2003) MATHCrossRef
155.
Randen, T., Husøy, J.H.: Multichannel filtering for image texture segmentation. Opt. Eng. 33(2), 2617–2625 (1994) CrossRef
156.
Randen, T., Husøy, J.H.: Filtering for texture classification: A comparative study. IEEE Trans. Pattern Anal. Mach. Intell. 21(4), 291–310 (1999) CrossRef
157.
Reddi, S.S.: Radial and angular moment invariants for image identification. IEEE Trans. Pattern Anal. Mach. Intell. 3(2), 240–242 (1981) CrossRef
158.
Reddy, B.S., Chatterji, B.: An FFT-based technique for translation, rotation and scale invariant image registration. IEEE Trans. Image Process. 5(8), 1266–1271 (1996) CrossRef
159.
Reed, T.R., Du Buf, J.M.H.: A review of recent texture segmentation and feature extraction techniques. CVGIP, Image Underst. 57(3), 359–372 (1993) CrossRef
160.
Reisfeld, D.: The constrained phase congruency feature detector: Simultaneous location, classification, and scale determination. Pattern Recognit. Lett. 17(11), 1161–1169 (1996) CrossRef
161.
Reisfeld, D., Wolfson, H., Yeshurun, Y.: Detection of interest points using symmetry. In: Proc. 3rd Int’l Conf. Computer Vision, Osaka, Japan, pp. 62–65 (1990)
162.
Reisfeld, D., Wolfson, H., Yeshurun, Y.: Context-free attention operators: The generalized symmetry transform. Int. J. Comput. Vis. 14(2), 119–130 (1995) CrossRef
163.
Rohr, K.: Extraction of 3D anatomical point landmarks based on invariance principles. Pattern Recognit. 32, 3–15 (1999) CrossRef
164.
Salvador, E., Cavallaro, A., Ebrahimi, T.: Cast shadow segmentation using invariant color features. Comput. Vis. Image Underst. 95, 238–259 (2004) CrossRef
165.
Sarfaraz, M.S., Hellwich, O.: Estimation in face recognition across pose scenarios. In: Proc. Int’l Conf. Computer Vision Theory and Applications, vol. 1, pp. 235–242 (2008)
166.
Sarkar, N., Chaudhuri, B.B.: An efficient differential box-counting approach to compute fractal dimension of image. IEEE Trans. Syst. Man Cybern. 24, 115–120 (1994) CrossRef
167.
Sastry, Ch.S., Pujari, A.K., Deekshatulu, B.L., Bhagvati, C.: A wavelet based multiresolution algorithm for rotation invariant feature extraction. Pattern Recognit. Lett. 25, 1845–1855 (2004) CrossRef
168.
Saupe, D.: Algorithms for random fractals. In: Peitgen, H., Saupe, D. (eds.) The Science of Fractal Images, pp. 71–136. Springer, New York (1988) CrossRef
169.
Schaffalizky, F., Zisserman, A.: Viewpoint invariant texture matching and wide baseline stereo. In: Proc. Int’l Conf. Computer Vision, vol. 2, pp. 636–643 (2001)
170.
Schaffalitzky, F., Zisserman, A.: Multi-view matching for unordered image sets. In: European Conf. Computer Vision, pp. 414–431 (2002)
171.
Schiele, B., Crowley, J.L.: Probabilistic object recognition using multidimensional receptive field histograms. In: Proc. 13th Int’l Conf. Pattern Recognition, vol. 2, pp. 50–54 (1996) CrossRef
172.
Schiele, B., Crowley, J.L.: Object recognition using multidimensional receptive field histograms. In: Proc. European Conf. Computer Vision (ECCV), vol. 1, pp. 610–619 (1996)
173.
Selesnick, I.W., Baraniuk, R.G., Kingsburg, N.G.: The dual-tree complex wavelet transform—a coherent framework for multiscale signal and image processing. IEEE Signal Process. Mag. 22(6), 123–151 (2005) CrossRef
174.
Serre, T., Wolf, L., Poggio, T.: Object recognition with features inspired by visual cortex. In: Proc. Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 994–1000 (2005)
175.
Shannon, C.E.: The mathematical theory of communication. In: Shannon, C.E., Weaver, W. (eds.) The Mathematical Theory of Communication, pp. 29–125. University of Illinois Press, Urbana (1949), reprint (1998)
176.
Shen, D., Ip, H.H.S.: Discriminative wavelet shape descriptors for recognition of 2-D patterns. Pattern Recognit. 32, 151–165 (1999) CrossRef
177.
Shen, B., Sethi, I.K.: Direct feature extraction from compressed images. In: SPIE Conf. Storage and Retrieval from Image and Video Databases IV, vol. 2670 (1996)
178.
Shen, J., Shen, W., Shen, D.: On geometric and orthogonal moments. Int. J. Pattern Recognit. Artif. Intell. 14(7), 875–894 (2000) CrossRef
179.
Shi, J., Tomasi, C.: Good features to track. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, Seattle, WA, pp. 593–600 (1994)
180.
Shokoufandeh, A., Marsic, I., Dickinson, S.J.: View-based object recognition using saliency maps. Image Vis. Comput. 17(5/6), 445–460 (1999) CrossRef
181.
Shu, H., Zhang, H., Haigron, P., Luo, L.: Fast computation of Tchebichef moments for binary and grayscale images. IEEE Trans. Image Process. 19(12), 3171–3180 (2010) MathSciNetCrossRef
182.
Sirovich, L., Kirby, M.: Low-dimensional procedure for the characterization of human faces. J. Opt. Soc. Am. A 4(3), 519–524 (1987) CrossRef
183.
Soille, P., Rivest, J.-F.: On the validity of fractal dimension measurements in image analysis. J. Vis. Commun. Image Represent. 7(3), 217–229 (1996) CrossRef
184.
Staring, M., van der Heide, U.A., Klein, S., Viergever, M.A., Pluim, J.P.W.: Registration of cervical MRI using multifeature mutual information. IEEE Trans. Med. Imaging 28(9), 1412–1421 (2009) CrossRef
185.
Stewart, G.W.: Introduction to Matrix Computations, p. 318. Academic Press, New York (1973) MATH
186.
187.
Swain, M.J., Ballard, D.H.: Color indexing. Int. J. Comput. Vis. 7(1), 11–32 (1991) CrossRef
188.
Szegö, G.: Orthogonal Polynomials, 4th edn. Am. Math. Soc., Providence (1981)
189.
Tamura, H., Mori, S., Yamawaki, T.: Texture features corresponding to visual perception. IEEE Trans. Syst. Man Cybern. 8(6), 460–473 (1978) CrossRef
190.
Tang, F., Lim, S.H., Chang, N.L., Tao, H.: A novel feature descriptor invariant to complex brightness changes. In: Proc. Computer Vision and Pattern Recognition, pp. 2631–2638 (2009)
191.
Tango, W.J.: The circle polynomials of Zernike and their application in optics. Appl. Opt. 13, 327–332 (1977)
192.
193.
Teh, C.-H., Chin, R.T.: On image analysis by the methods of moments. IEEE Trans. Pattern Anal. Mach. Intell. 10(4), 496–513 (1988) MATHCrossRef
194.
ter Haar Romeny, B.M., Florack, L.M.J., Salden, A.H., Viergever, M.A.: High order differential structure of images. In: 13th Int’l Conf. Information Processing in Medical Imaging, pp. 77–93 (1993) CrossRef
195.
Tewfik, A.H., Kim, M.: Correlation structure of the discrete wavelet coefficients of fractional Brownian motion. IEEE Trans. Inf. Theory 38, 904–909 (1992) MathSciNetMATHCrossRef
196.
Tian, Y., Tan, T., Wang, Y., Fang, Y.: Do singular values contain adequate information for face recognition. Pattern Recognit. 36(3), 649–655 (2003) CrossRef
197.
Trajković, M., Hedley, M.: Fast corner detection. Image Vis. Comput. 16, 75–87 (1998) CrossRef
198.
Tuceryan, M., Jain, A.K.: Texture analysis. In: Chen, C.H., Pau, L.F., Wang, P.S.P. (eds.) The Handbook of Pattern Recognition and Computer Vision, 2nd edn., pp. 207–248. World Scientific, Singapore (1998)
199.
Turk, M., Pentland, A.P.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–96 (1991) CrossRef
200.
Turner, M.R.: Texture discrimination by Gabor functions. Biol. Cybern. 55, 71–82 (1986)
201.
Tuytelaars, T., van Gool, L.: Content-based image retrieval based on local affinely invariant regions. In: Proc. Int. Conf. on Visual Information Systems, pp. 493–500 (1999) CrossRef
202.
Tuytelaars, T., van Gool, L.: Matching widely separated views based on affine invariant regions. Int. J. Comput. Vis. 59(1), 61–85 (2004) CrossRef
203.
Tuyterlaars, T., van Gool, L.: Wide baseline stereo matching based on local, affinely invariant regions. In: British Machine Vision Conference (2000)
204.
Tuytelaars, T., van Gool, L., D’haene, L., Koch, R.: Matching of affinely invariant regions for visual sevoing. In: Int’l Conf. Robotics and Automation, pp. 1601–1606 (1999)
205.
Ullman, S., Vidal-Naquet, M., Sali, E.: Visual features of intermediate complexity and their use in classification. Nat. Neurosci. 5(7), 682–687 (2002)
206.
Unser, M.: Sum and difference histograms for texture classification. IEEE Trans. Pattern Anal. Mach. Intell. 8(1), 118–125 (1986) CrossRef
207.
van Gool, L., Moons, T., Ungureanu, D.: Affine/photometric invariants for planar intensity patterns. In: Proc. European Conference on Computer Vision, pp. 642–651 (1996)
208.
Voss, R.: Fractals in nature: From characterization to simulation. In: Peitgen, H., Saupe, D. (eds.) The Science of Fractal Images, pp. 21–70. Springer, New York (1988) CrossRef
209.
Walker, K.N., Cootes, T.F., Taylor, C.J.: Correspondence using distinct points based on image invariants. In: British Machine Vision Conference, pp. 540–549 (1997)
210.
Walker, K.N., Cootes, T.F., Taylor, C.J.: Locating salient facial features using image invariants. In: Int. Conf. Automatic Face and Gesture Recognition, Nara, Japan (1998)
211.
212.
Wang, H., Brady, M.: A practical solution to corner detection. In: Proc. 5th Int’l Conf. Image Processing, vol. 1, pp. 919–923 (1994)
213.
Wang, H., Brady, M.: Real-time corner detection algorithm for motion estimation. Image Vis. Comput. 13(9), 695–703 (1995) CrossRef
214.
Wang, G., Wang, S.: Recursive computation of Tchebichef moment and its inverse transform. Pattern Recognit. 39, 47–56 (2006) CrossRef
215.
Wang, W., Li, J., Huang, F., Feng, H.: Design and implementation of Log-Gabor filter in fingerprint image enhancement. Pattern Recognit. Lett. 29, 301–308 (2008) MATHCrossRef
216.
Wang, Y.B., Zhang, B., Yao, T.S.: Moment invariants of restricted projective transformations. In: Int’l Sym. Information Science and Engineering, vol. 1, pp. 249–253 (2008)
217.
Wee, C.-Y., Paramesran, R.: On the computational aspects of Zernike moments. Image Vis. Comput. 25, 967–980 (2007) CrossRef
218.
Weszka, J.S., Dyer, C.R., Rosenfeld, A.: A comparative study of texture measures for terrain classification. IEEE Trans. Syst. Man Cybern. 6(4), 269–285 (1976) MATH
219.
Wornell, G.W.: Wavelet-based representations for the 1/f family of fractal processes. Proc. IEEE 81, 1428–1450 (1993) CrossRef
220.
Worthy, L., Sinzinger, E.: Scene identification using invariant radial feature descriptors. In: Proc. 8th Int’l Workshop Image Analysis for Multimedia Interactive Service, pp. 39–43 (2007) CrossRef
221.
Wu, Y., Shen, J.: Properties of orthogonal Gaussian–Hermite and their applications. EURASIP J. Appl. Signal Process. 4, 588–599 (2005) MathSciNet
222.
Wu, C.-M., Chen, Y.-C., Hsieh, K.-S.: Texture features for classification of ultrasonic liver images. IEEE Trans. Med. Imaging 11(2), 141–152 (1992) CrossRef
223.
224.
Yap, P.-T., Paramesran, R., Ong, S.-H.: Image analysis by Krawtchouk moments. IEEE Trans. Image Process. 12(11), 1367–1377 (2003) MathSciNetCrossRef
225.
You, J., Cohen, H.A.: Classification and segmentation of rotated and scaled textured images using texture ‘tuned’ masks. Pattern Recognit. 26(2), 245–258 (1993) CrossRef
226.
Yuanbin, W., Bin, Z., Tianshun, Y.: Projective invariants of co-moments of 2D images. Pattern Recognit. 43, 3233–3242 (2010) MATHCrossRef
227.
Zhang, Y., Chen, T.: Efficient kernels for identifying unbounded-order spatial features. In: Proc. Conf. Computer Vision and Pattern Recognition, pp. 1762–1769 (2009)
228.
Zhang, L., Ghosh, B.K.: Geometric feature based 2.5D map building and planning with laser, sonar, and tactile sensors. In: Proc. Int’l Conf. Intelligent Robots and Systems, vol. 1, pp. 115–120 (2000)
229.
Zhang, X.-W., Song, J.-Q., Lyu, M.R., Cai, S.-J.: Extraction of karyocytes and their components from microscopic bone marrow images based on regional color features. Pattern Recognit. 37, 351–361 (2004) MATHCrossRef
230.
Zhang, J., Marszalek, M., Lazebnik, S., Schmid, C.: Local features and kernels for classification of texture and object categories: A comprehensive study. Int. J. Comput. Vis. 73(2), 213–238 (2007) CrossRef
231.
Zhang, B., Shan, S., Chen, X., Gao, W.: Histogram of Gabor phase patterns (HGPP): A novel object representation approach for face recognition. IEEE Trans. Image Process. 16(1), 57–68 (2007) MathSciNetCrossRef
232.
Zhang, H., Shu, H., Han, G.N., Gouenou, G., Luo, L., Coatrieux, J.L.: Blurred image recognition by Legendre moment invariants. IEEE Trans. Image Process. 19(3), 596–611 (2010) MathSciNetCrossRef
233.
Zhou, X.S., Rui, Y., Huang, T.S.: Water-filling: A novel way for image structural feature extraction. In: Proc. Int’l Conf. Image Processing, vol. 2, pp. 570–574 (1999)
234.
Zhu, H., Shu, H., Xia, T., Luo, L., Coatrieux, J.L.: Translation and scale invariants of Tchebichef moments. Pattern Recognit. 40, 2530–2542 (2007) MATHCrossRef
Metadata
Title
Feature Extraction
Author
Prof. A. Ardeshir Goshtasby
Copyright Year
2012
Publisher
Springer London
Book
Image Registration

Print ISBN: 978-1-4471-2457-3

Electronic ISBN: 978-1-4471-2458-0

Copyright Year: 2012

DOI
https://doi.org/10.1007/978-1-4471-2458-0_4

Premium Partner

    Image Credits