体育赛事投注记录

体育赛事投注记录advertisement

MPEG-7 Image Color Features

  • Jyotismita ChakiEmail author
  • Nilanjan Dey
Chapter
  • 20 Downloads
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Abstract

This chapter delivers an outline of MPEG-7 color descriptors. The choice of these color descriptors is influenced by various factors [1, 2, 3]. These include (a) their capacity to classify the likeness of perceptual colors, assessed by descriptor performance in matching video segments and images using color features, (b) minimum complexity of the related feature extraction and matching procedures, because MPEG-7 systems must be capable of handling recovery tasks through broad multimedia repositories, or small mobile devices with minimal computational power, (c) coded description sizes that have a significant role in indexing and distributing descriptors through limited bandwidth networks, and (d) the descriptors’ scalability and interoperability.

References

  1. 1.
    Babu C, Shanthi M (2012) An efficient image compression technique by extracting features in the image. Bonfring Int J Ad Image Process 2:95–99
  2. 2.
    Histograms CII (2013) Bi-level classification of color indexed image histograms for content based image retrieval. J Comput Sci 9(3):343–349.  
  3. 3.
    Mohapatra DP, Patnaik S (eds) (2013). Intelligent computing, networking, and informatics: proceedings of the international conference on advanced computing, networking, and informatics. Springer Science & Business Media, India, vol 243, June 2013
  4. 4.
    Pavithra LK, Sharmila TS (2019) An efficient seed points selection approach in dominant color descriptors (DCD). Cluster Comput 22(4):1225–1240.  
  5. 5.
    Czapiewski P, Forczmański P, Okarma K, Frejlichowski D, Hofman R (2016) Clothing similarity estimation using dominant color descriptor and SSIM index. In: Proceedings of the 9th international conference on computer recognition systems CORES 2015. Springer, Cham, pp 491–500
  6. 6.
    Rejeb IB, Ouni S, Zagrouba E (2017) Image retrieval using spatial dominant color descriptor. In: 2017 IEEE/ACS 14th international conference on computer systems and applications (AICCSA). Hammamet, pp 788–795.  
  7. 7.
    Algur SP, Ayachit NH (2016) A channelized binning method for extraction of dominant color pixel value. arXiv preprint
  8. 8.
    Georgescu FA, Răducanu D, Datcu M (2017) New MPEG-7 scalable color descriptor based on polar coordinates for multispectral earth observation image analysis. IEEE Geosci Remote Sens Lett 14(7):987–991.  
  9. 9.
    Chantharainthron P, Panthuwadeethorn S, Phimoltares S (2017) Robust video editing detection using scalable color and color layout descriptors. In: 2017 14th international joint conference on computer science and software engineering (JCSSE). Nakhon Si Thammarat, pp 1–6.  
  10. 10.
    Imran M, Hashim R, Irtaz A, Mahmood A, Abdullah U (2016) Class wise image retrieval through scalable color descriptor and edge histogram descriptor. Int J Adv Appl Sci 3(12):32–36.  
  11. 11.
    Dewi AF, Arnia F, Muharar R (2017) Effectiveness of MPEG-7 color features in clothing retrieval. Bull Electr Eng Inf 6(2):166–173.  
  12. 12.
    Aghamaleki JA, Behrad A (2018) Detecting double compressed MPEG videos with the same quantization matrix and synchronized group of pictures structure. J Electron Imaging 27(1):013031.  
  13. 13.
    Sikora T (2018) MPEG digital video coding standards. In: Compressed video over networks. CRC Press, pp 45–88
  14. 14.
    Busari KA, Adamu ID, Ali MH, Busari TA, Afolabi MA, Kashimbila MM (2018) Simulation of the effect of bit assignment to multi-hypothesis pictures per group for motion compensated video compression (MCVC). Bayero J Pure Appl Sci 11(1):1–7.  
  15. 15.
    Pandey S, Dwivedy P, Meena S, Potnis A (2017) A survey on key frame extraction methods of a MPEG video. In: 2017 international conference on computing, communication and automation (ICCCA). Greater Noida, pp 1192–1196.  
  16. 16.
    Chantharainthron P, Panthuwadeethorn S, Phimoltares S (2017) Robust video editing detection using scalable color and color layout descriptors. In: 2017 14th IEEE international joint conference on computer science and software engineering (JCSSE). Nakhon Si Thammarat, pp 1–6.  
  17. 17.
    Tsai HH, Chang BM, Lo PS, Peng JY (2016) On the design of a color image retrieval method based on combined color descriptors and features. In: 2016 first IEEE international conference on computer communication and the internet (ICCCI). Wuhan, pp 392–395.  
  18. 18.
    Watcharasing J, Thiralertphanich T, Panthuwadeethorn S, Phimoltares S (2019) Classification of fruit in a box (FIB) using hybridization of color and texture features. In: 2019 16th international joint conference on computer science and software engineering (JCSSE). Chonburi, pp 303–308.  
  19. 19.
    Lee YH, Bang SI (2019) Improved image retrieval and classification with combined invariant features and color descriptor. J Ambient Intell Humanized Comput 10(6):2255–2264.  
  20. 20.
    Abdelali AB, Hannachi M, Touil L, Mtibaa A (2017) Adequation and hardware implementation of the color structure descriptor for real-time temporal video segmentation. J Real-Time Image Proc 13(4):739–758.  
  21. 21.
    Florea C, Toca C, Gieseke F (2017) Artistic movement recognition by boosted fusion of color structure and topographic description. In: 2017 IEEE winter conference on applications of computer vision (WACV). Santa Rosa, pp 569–577.  
  22. 22.
    Siswantoro J, Arwoko H, Widiasri M (2019) Image based indonesian fruit recognition using MPEG-7 color structure descriptor and k-Nearest neighbor. In: International conference on informatics, technology, and engineering 2019. The Anvaya Resort in Denpasar
  23. 23.
    Yu H, Yang W, Xia GS, Liu G (2016) A color-texture-structure descriptor for high-resolution satellite image classification. Remote Sens 8(3):259.  

Copyright information

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.School of Information Technology and EngineeringVellore Institute of TechnologyVelloreIndia
  2. 2.Department of Information TechnologyTechno India College of TechnologyKolkataIndia

Personalised recommendations