Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Background Modeling Using Temporal-Local Sample Density Outlier Detection Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Content Aware Image Size Reduction Using Low Energy Maps for Reduced Distortion

verfasst von : Pooja Solanki, Charul Bhatnagar, Anand Singh Jalal, Manoj Kumar

Erschienen in: Proceedings of International Conference on Computer Vision and Image Processing

Verlag: Springer Singapore

Einloggen

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

search-config
loading …

Abstract

On different devices images are often viewed with different resolutions which require image resizing. Resizing images often affects the quality of the images. To better resize images to different resolutions content aware image resizing should be done so that important features are preserved. Seam carving is one such content aware image resizing technique. In this work seam carving is used to downsize an image. This is achieved by carving out an optimal seam (either vertical or horizontal), which contains less information. Each seam removes a pixel from every row (or column) to reduce the height (or width) of the image. To prevent distortion resulting from uniform seam carving, we propose an algorithm that uses a new energy gradient function. In this method minimum of three neighboring pixels is calculated in both energy map and cumulative map and these values are added to find the value of pixel for the new cost matrix.

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!

Jetzt informieren

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!

Jetzt informieren

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!

Jetzt informieren
Vorheriges Kapitel Pre- and Post-fingerprint Skeleton Enhancement for Minutiae Extraction
Nächstes Kapitel Artificial Immune Hybrid Photo Album Classifier
Literatur
1.
Fan, X., Xie, X., Ma, W. Y., Zhang, H. J., & Zhou, H. Q.: Visual attention based image browsing on mobile devices. In Proceedings of IEEE International Conference on Multimedia and Expo, ICME’03. Vol. 1, pp. I-53, (2003).
2.
Chen, L. Q., Xie, X., Fan, X., Ma, W. Y., Zhang, H. J., & Zhou, H. Q.: A visual attention model for adapting images on small displays. Multimedia systems. vol. 9, no. 4, pp. 353–364, (2003).
3.
R Samadani, R., Lim, S. H., & Tretter, D.: Representative image thumbnails for good browsing. In IEEE International Conference on Image Processing, ICIP 2007. Vol. 2, pp. II-193, (2007).
4.
Liu, F., & Gleicher, M.: Automatic image retargeting with fisheye-view warping. In Proceedings of the 18th annual ACM symposium on User interface software and technology. pp. 153–162, (2005).
5.
Setlur, V., Takagi, S., Raskar, R., Gleicher, M., & Gooch, B.: Automatic image retargeting. In Proceedings of the 4th ACM international conference on Mobile and ubiquitous multimedia. pp. 59–68, (2005).
6.
Ren, T., Guo, Y., Wu, G., & Zhang, F.: Constrained sampling for image retargeting. In IEEE International Conference on Multimedia and Expo. pp. 1397–1400, (2008).
7.
Wang, Y. S., Tai, C. L., Sorkine, O., & Lee, T. Y.: Optimized scale-and-stretch for image resizing. ACM Transactions on Graphics. Vol. 27, no.5, pp. 118, (2008).
8.
Mansfield, A., Gehler, P., Van Gool, L., & Rother, C.: Visibility maps for improving seam carving. In Trends and Topics in Computer Vision, Springer Berlin Heidelberg, pp. 131–144, (2012).
9.
Rubinstein, M., Shamir, A., & Avidan, S.: Improved seam carving for video retargetting. In ACM transactions on graphics. Vol. 27, No. 3, pp. 16, (2008).
10.
Hwang, D. S., & Chien, S. Y.: Content-aware image resizing using perceptual seam carving with human attention model. In IEEE International Conference on Multimedia and Expo. pp. 1029–1032, (2008).
11.
Criminisi, A., Perez, P., & Toyama, K.: Object removal by exemplar-based inpainting. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2, pp. II-721, (2003).
12.
Avidan, S., & Shamir, A.: Seam carving for content-aware image resizing, In ACM Transactions on graphics, Vol. 26, No. 3, p. 10, (2007).
13.
Achanta, R., & Süsstrunk, S.: Saliency detection for content-aware image resizing. In 16th IEEE International Conference on Image Processing (ICIP). pp. 1005–1008, (2009).
14.
Domingues, D., Alahi, A., & Vandergheynst, P.: Stream carving: an adaptive seam carving algorithm. In 17th IEEE International Conference on Image Processing (ICIP). pp. 901–904, (2010).
15.
He, Z., Gao, M., Yu, H., Ye, X., Zhang, L., & Ma, G.: A new improved seam carving content aware image resizing method. In 8th IEEE Conference on Industrial Electronics and Applications (ICIEA). pp. 738–741, (2013).
16.
Frankovich, M., & Wong, A.: Enhanced seam carving via integration of energy gradient functionals. IEEE Signal Processing Letters. vol. 18, no. 6, pp. 375–378, (2011).
Metadaten
Titel
Content Aware Image Size Reduction Using Low Energy Maps for Reduced Distortion
verfasst von
Pooja Solanki
Charul Bhatnagar
Anand Singh Jalal
Manoj Kumar
Copyright-Jahr
2017
Verlag
Springer Singapore
Buch
Proceedings of International Conference on Computer Vision and Image Processing

Print ISBN: 978-981-10-2103-9

Electronic ISBN: 978-981-10-2104-6

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-981-10-2104-6_42

Neuer Inhalt

    Bildnachweise