Skip to main content

2016 | OriginalPaper | Buchkapitel

Steerable Texture Descriptor for an Effective Content-Based Medical Image Retrieval System Using PCA

verfasst von : B. Jyothi, Y. MadhaveeLatha, P. G. Krishna Mohan, V. S. K. Reddy

Erschienen in: Proceedings of the Second International Conference on Computer and Communication Technologies

Verlag: Springer India

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Digital images have increased in quantity especially in the medical field used for diagnostics. Content-Based Medical Image Retrieval System will retrieve similar medical images from large database based on their visual features like texture, color, and shape. This paper focuses a novel method to increase the performance using Boundary detection, Steerable filter, and Principal Component Analysis. The content of the image was extracted with the help of region-based texture descriptor using steerable decomposition followed by extracting Principle Component Analysis which has better feature representation capabilities. The similar medical images are retrieved by comparing the extracted feature vector of the given query image with the corresponding database feature vectors using Euclidian distance as a similarity measure. The effectiveness of the proposed method is evaluated and exhibited via various types of medical images. With the experimental results, it is obvious that the region-based feature extraction method outperforms the direct feature extraction-based image retrieval system.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

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!

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!

Literatur
1.
Zurück zum Zitat Müller, H., Michoux, N., Bandon, D., Geissbuhler, A.: A review of content-based image retrieval systems in medical applications-clinical benefits and future directions. Med. Inform. 1, 73 (2004) Müller, H., Michoux, N., Bandon, D., Geissbuhler, A.: A review of content-based image retrieval systems in medical applications-clinical benefits and future directions. Med. Inform. 1, 73 (2004)
2.
Zurück zum Zitat Khoo, L.A., Taylor, P., Given-Wilson, R.M.: Computer-aided detection in the United Kingdom national breast screening programme: prospective study. Radiology 237, 444–449 (2005)CrossRef Khoo, L.A., Taylor, P., Given-Wilson, R.M.: Computer-aided detection in the United Kingdom national breast screening programme: prospective study. Radiology 237, 444–449 (2005)CrossRef
3.
Zurück zum Zitat Chun, Y.D., Kim, N.C., Jang, I.H.: Content-based image retrieval using multiresolution color and texture features. IEEE Trans. Multimedia 10(6), 1073–1084 (2008)CrossRef Chun, Y.D., Kim, N.C., Jang, I.H.: Content-based image retrieval using multiresolution color and texture features. IEEE Trans. Multimedia 10(6), 1073–1084 (2008)CrossRef
4.
Zurück zum Zitat Somkantha, K., Theera-Umpon, N.: Boundary detection in medical images using edge following algorithm based on intensity gradient and texture gradient features. Proc. IEEE Trans. Biomed. Eng. 58(3), 567–573 (2011)CrossRef Somkantha, K., Theera-Umpon, N.: Boundary detection in medical images using edge following algorithm based on intensity gradient and texture gradient features. Proc. IEEE Trans. Biomed. Eng. 58(3), 567–573 (2011)CrossRef
5.
Zurück zum Zitat Veeralakshmi, S., Sivagami, S.V., Devi, V.V., Udhaya, R.: Boundary exposure using intensity and texture gradient features. IOSR J. Comput. Eng. (IOSRJCE) ISSN: 2278-0661, 8(1), 28–33 (Nov–Dec 2012). ISBN: 2278-8727, www.iosrjournals.org Veeralakshmi, S., Sivagami, S.V., Devi, V.V., Udhaya, R.: Boundary exposure using intensity and texture gradient features. IOSR J. Comput. Eng. (IOSRJCE) ISSN: 2278-0661, 8(1), 28–33 (Nov–Dec 2012). ISBN: 2278-8727, www.​iosrjournals.​org
6.
Zurück zum Zitat Jacob, M., Unser, M.: Design of steerable filters for feature detection using canny like criteria. IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1007–1019 (2004)CrossRef Jacob, M., Unser, M.: Design of steerable filters for feature detection using canny like criteria. IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1007–1019 (2004)CrossRef
7.
Zurück zum Zitat Wang, X.-Y., Yu, Y.-J., Yang, H.-Y.: An effective image retrieval scheme using color, texture and shape features. Comput. Stan. Interfaces CSI-02706 33(1), 59–68 (2011) Wang, X.-Y., Yu, Y.-J., Yang, H.-Y.: An effective image retrieval scheme using color, texture and shape features. Comput. Stan. Interfaces CSI-02706 33(1), 59–68 (2011)
8.
Zurück zum Zitat Navaz1, A.S.S., Dhevi sri, T., Mazumder, P.: Face recognition using principal component analysis and neural networks. Int. J. Comput. Netw. Wirel. Mobile Commun. 3(1), 245–256 (Mar 2013). ISSN: 2250-1568 Navaz1, A.S.S., Dhevi sri, T., Mazumder, P.: Face recognition using principal component analysis and neural networks. Int. J. Comput. Netw. Wirel. Mobile Commun. 3(1), 245–256 (Mar 2013). ISSN: 2250-1568
9.
Zurück zum Zitat El-Naga, I., Yang, Y., Galatsanos, N.P., Nishikawa, R.M., Wernick, M.N.: A similarity learning approach to content-based image retrieval: application to digital mammography. IEEE Trans. Medical Imaging 23(10), 1233–1244 (2004)CrossRef El-Naga, I., Yang, Y., Galatsanos, N.P., Nishikawa, R.M., Wernick, M.N.: A similarity learning approach to content-based image retrieval: application to digital mammography. IEEE Trans. Medical Imaging 23(10), 1233–1244 (2004)CrossRef
10.
Zurück zum Zitat Arevalillo-Herráez, M., Domingo, J., Ferri, F.J.: Combining similarity measures in content-based image retrieval. Pattern Recognit. Lett. 29, 2174–2181 (2008)CrossRef Arevalillo-Herráez, M., Domingo, J., Ferri, F.J.: Combining similarity measures in content-based image retrieval. Pattern Recognit. Lett. 29, 2174–2181 (2008)CrossRef
11.
Zurück zum Zitat Rasli, R.M, Muda, T.Z.T., Yusof, Y.: Comparative analysis of content based image retrieval techniques using color histogram: a case study of GLCM and K-means clustering. In; 3rd International Conference on Intelligent Systems, Modelling and Simulation (ISMS), pp. 283–286 (2012). ISBN: 978-1-4673-0886-1 Rasli, R.M, Muda, T.Z.T., Yusof, Y.: Comparative analysis of content based image retrieval techniques using color histogram: a case study of GLCM and K-means clustering. In; 3rd International Conference on Intelligent Systems, Modelling and Simulation (ISMS), pp. 283–286 (2012). ISBN: 978-1-4673-0886-1
12.
Zurück zum Zitat Dubey, R.S., Choubey, R., Bhattacharjee, J.: Multi feature content based image retrieval. Int. J. Comput. Sci. Eng. 02(06) (2010). ISSN : 0975-3397 2145 2145-2149 Dubey, R.S., Choubey, R., Bhattacharjee, J.: Multi feature content based image retrieval. Int. J. Comput. Sci. Eng. 02(06) (2010). ISSN : 0975-3397 2145 2145-2149
Metadaten
Titel
Steerable Texture Descriptor for an Effective Content-Based Medical Image Retrieval System Using PCA
verfasst von
B. Jyothi
Y. MadhaveeLatha
P. G. Krishna Mohan
V. S. K. Reddy
Copyright-Jahr
2016
Verlag
Springer India
DOI
https://doi.org/10.1007/978-81-322-2517-1_29