Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2017, Cilt: 5 Sayı: 2, 66 - 72, 01.09.2017
https://doi.org/10.17694/bajece.336217

Öz

Kaynakça

  • [1] Nakamura, J. (Ed.). (2016). Image sensors and signal processing for digital still cameras. CRC press.
  • [2] Rao, K. R. (2016, September). High efficiency video coding. In Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2016 (pp. 11-11). IEEE.
  • [3] Wolf, W., (1996), “Key Frame Selection by Motion Analysis”, Proceeding of IEEE International, Conference on Acoustics, Speech and Signal Processing, Atlanta, GA, 1228-1231.
  • [4] Dufaux, Frédéric, and Fabrice Moscheni. "Segmentation-based motion estimation for second generation video coding techniques." Video Coding. Springer US, 1996. 219-263.
  • [5] Zhang, Hong J., Jian H. Wu, and Stephen W. Smoliar. (1997), "System for automatic video segmentation and key frame extraction for video sequences having both sharp and gradual transitions." U.S. Patent No. 5,635,982. 3 Jun. 1997.
  • [6] Huang, C. L., & Liao, B. Y. (2001). A robust scene-change detection method for video segmentation. IEEE Transactions on Circuits and Systems for Video Technology, 11(12), 1281-1288.
  • [7] Lee, J., Lee, G. ve Kim, W., (2003), “Automatic video summarizing tool using MPEG-7 descriptors for personal video recorder”, IEEE Trans. on Cons. Elect, Vol 49, 49-742.
  • [8] Danila Potapov, Matthijs Douze, Zaid Harchaoui, Cordelia Schmid. Category-specific video summarization. ECCV 2014 - European Conference on Computer Vision, Sep 2014, Zurich, Switzerland, Springer, 2014.
  • [9] Zhang, L., Xia, Y., Mao, K., Ma, H., & Shan, Z. (2015). An effective video summarization framework toward handheld devices. Industrial Electronics, IEEE Transactions on, 62(2), 1309-1316.
  • [10] Wu, C., Zhang, L., & Du, B. (2017). Kernel slow feature analysis for scene change detection. IEEE Transactions on Geoscience and Remote Sensing, 55(4), 2367-2384.
  • [11] Marques, Oge. Practical image and video processing using MATLAB. John Wiley & Sons, 2011.
  • [12] Umbaugh, Scott E. Digital image processing and analysis: human and computer vision applications with CVIPtools. CRC press, 2016.
  • [13] Lena Söderbergt, Image Processing Benchmark image, 1973. URL: tps://en.wikipedia.org/wiki/Lenna, taken date: 06/02/2017.
  • [14] Mousavizadegan, M., & Mohabatkar, H. (2016). An Evaluation on Different Machine Learning Algorithms for Classification and Prediction of Antifungal Peptides. Medicinal Chemistry, 12(8), 795-800.

Scene Change Detection using Different Color Pallets and Performance Comparison

Yıl 2017, Cilt: 5 Sayı: 2, 66 - 72, 01.09.2017
https://doi.org/10.17694/bajece.336217

Öz

In the world of massive uploaded videos, to be able to cover the content
of a video at a glance becomes a necessity since there is no enough time to
watch the whole video for an individual. Looking at frames of different scenes
in a video gives a brief idea of the content, when each different scene images
are listed to be checked by the user. In this study, an approach using various
color palettes is proposed to be able to detect the different scenes of a
video. In the proposed method, color histogram values of sequential frames
firstly are calculated. If the difference in the histogram values of the pair
frames in sequence is over a threshold value (percentage of change), scene
change is detected. In the experimental studies, 3-Bit RGB (Red Green Blue),
6-Bit RGB, 8-Bit RGB, 9-Bit RGB, 1-Bit Binary, 4-Bit Gray, and 8-Bit Gray
palettes are implemented over a list of video files and compared. In the comparisons
of palettes, accuracy, precision, recall, and F1-Score performance metrics are
used. In the performance accuracy controls, 6-Bit RGB color pallet with a
threshold level value of 35% has been experimented as the best of all.
 

Kaynakça

  • [1] Nakamura, J. (Ed.). (2016). Image sensors and signal processing for digital still cameras. CRC press.
  • [2] Rao, K. R. (2016, September). High efficiency video coding. In Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2016 (pp. 11-11). IEEE.
  • [3] Wolf, W., (1996), “Key Frame Selection by Motion Analysis”, Proceeding of IEEE International, Conference on Acoustics, Speech and Signal Processing, Atlanta, GA, 1228-1231.
  • [4] Dufaux, Frédéric, and Fabrice Moscheni. "Segmentation-based motion estimation for second generation video coding techniques." Video Coding. Springer US, 1996. 219-263.
  • [5] Zhang, Hong J., Jian H. Wu, and Stephen W. Smoliar. (1997), "System for automatic video segmentation and key frame extraction for video sequences having both sharp and gradual transitions." U.S. Patent No. 5,635,982. 3 Jun. 1997.
  • [6] Huang, C. L., & Liao, B. Y. (2001). A robust scene-change detection method for video segmentation. IEEE Transactions on Circuits and Systems for Video Technology, 11(12), 1281-1288.
  • [7] Lee, J., Lee, G. ve Kim, W., (2003), “Automatic video summarizing tool using MPEG-7 descriptors for personal video recorder”, IEEE Trans. on Cons. Elect, Vol 49, 49-742.
  • [8] Danila Potapov, Matthijs Douze, Zaid Harchaoui, Cordelia Schmid. Category-specific video summarization. ECCV 2014 - European Conference on Computer Vision, Sep 2014, Zurich, Switzerland, Springer, 2014.
  • [9] Zhang, L., Xia, Y., Mao, K., Ma, H., & Shan, Z. (2015). An effective video summarization framework toward handheld devices. Industrial Electronics, IEEE Transactions on, 62(2), 1309-1316.
  • [10] Wu, C., Zhang, L., & Du, B. (2017). Kernel slow feature analysis for scene change detection. IEEE Transactions on Geoscience and Remote Sensing, 55(4), 2367-2384.
  • [11] Marques, Oge. Practical image and video processing using MATLAB. John Wiley & Sons, 2011.
  • [12] Umbaugh, Scott E. Digital image processing and analysis: human and computer vision applications with CVIPtools. CRC press, 2016.
  • [13] Lena Söderbergt, Image Processing Benchmark image, 1973. URL: tps://en.wikipedia.org/wiki/Lenna, taken date: 06/02/2017.
  • [14] Mousavizadegan, M., & Mohabatkar, H. (2016). An Evaluation on Different Machine Learning Algorithms for Classification and Prediction of Antifungal Peptides. Medicinal Chemistry, 12(8), 795-800.
Toplam 14 adet kaynakça vardır.

Ayrıntılar

Bölüm Araştırma Makalesi
Yazarlar

Faruk Bulut

Shaira Osmanı Bu kişi benim

Yayımlanma Tarihi 1 Eylül 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 5 Sayı: 2

Kaynak Göster

APA Bulut, F., & Osmanı, S. (2017). Scene Change Detection using Different Color Pallets and Performance Comparison. Balkan Journal of Electrical and Computer Engineering, 5(2), 66-72. https://doi.org/10.17694/bajece.336217

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