문화기술의 융합 (The Journal of the Convergence on Culture Technology)

  • 제10권6호
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  • Pages.869-874
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  • 2024
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  • 2384-0358(pISSN)
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  • 2384-0366(eISSN)
국제문화기술진흥원 (The International Promotion Agency of Culture Technology)
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복소 색상 모델을 이용한 회전 불변 색상-모양 기술 방법

Rotation Invariant Color-Shape Description Method using Complex Color Model

  • 최민석 (삼육대학교 인공지능융합학부)
  • Minseok CHoi (Div. of A.I Convergence, Sahmyook University)
  • 투고 : 2024.09.15
  • 심사 : 2024.11.01
  • 발행 : 2024.11.30
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초록

다양한 디지털 장비의 보급과 통신 및 네트워크 기술의 발전, 그리고 개인형 미디어 서비스의 확산은 멀티미디어 콘텐츠의 생산 및 유통을 폭발적으로 증가시켰다. 이미지나 동영상 같은 멀티미디어 데이터의 인식 및 검색은 데이터의 물리적인 특징들을 분석하여 정량화하고 이를 비교하는 내용 기반 인식 및 검색 방법이 요구된다. 이미지의 내용 기반 검색에서는 색상과 모양이 중요한 시각적 특징이 된다. 본 논문에서는 색상 특징과 모양 특징을 통합하여 표현하기 위해 제안된 복소 색상 모델을 사용하여 색상이 공간적으로 분포된 모양을 이미지의 회전과 무관하게 표현하고 인식하는 방법을 제안한다. 복소 색상 모델에 따라 변환된 복소 색상 이미지에 대하여 회전 불변 모양 기술자를 적용하면 회전과 무관하게 색상-모양을 표현하고 인식할 수 있음을 실험을 통하여 확인하였다.

The spread of various digital devices, the development of communication and network technologies, and the spread of personal media services have led to an explosive increase in the production and distribution of multimedia content. Recognition and search of multimedia data such as images and videos requires a content-based recognition and search method that analyzes and quantifies the physical characteristics of the data and compares them. In content-based search of images, color and shape become important visual features. In this paper, a method to describe and search the spatial distribution of color regardless of image rotation using the complex color model to intergrate color and shape features is proposed. It was confirmed through experiments that by applying a rotation-invariant shape descriptor to a complex color image converted according to a complex color model, color-shape could be expressed and recognized regardless of rotation.

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참고문헌

  1. S. J. Kim, "The present and prospect of Online Video, Music service and Media Usage", Journal of Digital Contents Society, Vol. 16, No. 1, pp. 137-144, 2015, DOI: 10.9728/dcs.2015.16.1.137
  2. B. S. Kang, K. H. Lee, "Fire Alarm Solutions Through the Convergence of Image Processing Technology and M2M", Journal of the Korea Convergence Society, Vol. 7, No. 1, pp. 37-42, 2016, DOI: 10.15207/JKCS.2016.7.1.037
  3. T. Dharani, I. L. Aroquiaraj, "A Survey on Content Based Image Retrieval", IEEE, International Conference on Pattern Recognition, Informatics and Mobile Engineering, pp. 485-490, February, 2013, Salem, India, DOI: 10.1109/ICPRIME.2013.6496719
  4. M. G. Song, S. J. Jeong, S. H. Choi, K. M. Lee, "Celebrity-indexed video retrieval application using face recognition and tracking", Journal of Digital Contents Society, Vol. 19, No. 11, pp. 2049-2058, 2018, DOI: 10.9728/dcs.2018.19.11.2049
  5. Abul Abbas Barbhuiya, Ram Kumar Karsh, Rahul Jain, "A convolutional neural network and classical moments-based feature fusion model for gesture recognition", Multimedia Systems, Vol. 28, No. 5, pp. 1779-1792, 2022, DOI: 10.1007/s00530-022-00951-5
  6. Yangwei Cheng, Gongfa Li, Ming-Chao Yu, Du Jiang, Juntong Yun, Ying Liu, Yibo Liu, Disi Chen, "Gesture recognition based on surface electromyography-feature image", Concurrency and Computation: Practice and Experience, Vol. 33, No. 6, 08 October 2020, DOI: 10.1002/cpe.6051
  7. Quan, D., Wei, H., Wang, S., Lei, R., Duan, B., Li, Y., Hou, B., & Jiao, L, "Self-Distillation Feature Learning Network for Optical and SAR Image Registration", IEEE Transactions on Geoscience and Remote Sensing, Vol. 60, pp. 1-18., 2022, DOI: 10.1109/TGRS.2022.3173476
  8. Vankayalapati, H.D, Kuchibhotla, S, Chadalavada, M.S.K, Dargar, S.K, Anne, K.R, Kyandoghere, K. A, "Novel Zernike Moment-Based Real-Time Head Pose and Gaze Estimation Framework for Accuracy-Sensitive Applications", Sensors Vol. 22, 8449, 2022, DOI: 10.3390/s22218449
  9. A. Yoshitaka, T. Ichikawa, "A Survey on Content-Based Retrieval for Multimedia Databases", IEEE transactions on knowledge and data engineering, Vol. 11, No. 1, pp. 81-93, 1999, DOI: 10.1109/69.755617
  10. P. Napoletano, "Visual descriptors for content-based retrieval of remote-sensing images", International Journal of Remote Sensing, Vol. 39, No. 5, pp. 1343-1376, 2018, DOI: 10.1080/01431161.2017.1399472
  11. M. S. Choi, "Complex color model for efficient representation of color-shape in content-based image retrieval", Journal of Digital Convergence, Vol. 15, No. 4, pp. 267-273, 2016, DOI: 10.14400/JDC.2017.15.4.267
  12. J. Song, "Content-based Image Retrieval using HSV Color and Uniform Local Binary Patterns", Journal of Korean Institute of Information Technology, Vol. 12, No. 2, pp. 169-174, 2014, DOI: : 10.5909/JBE.2013.18.3.372
  13. Y. N. Liu, S. S. Zhang, Y. Sang, S. M. Wang, "Improving image retrieval by integrating shape and texture features", Multimedia Tools Application, Vol. 78, pp. 2525-2550, 2019, DOI: 10.1007/s11042-018-6386-6
  14. J. C. Chun, D. S. Kim, "A Contents-based Drug Image Retrieval System Using Shape Classification and Color Information", Journal of Internet Computing and Services, Vol. 12, No. 6, pp. 117-128, 2011.
  15. D. W. Kim, Y. J. Song, Y. G. Kim, J. H. Ahn, "Content-Based Image Retrieval using Region Feature Vector", The KIPS Transactions : Part B, Vol. 13, No. 1, pp. 47-52, 2006, DOI: 10.3745/KIPSTB.2006.13B.1.047
  16. A. Khotanzad, Y.H. Hong, "Invariant image recognition by Zernike moments", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 5, pp. 489-497, 1990, DOI: 10.1109/34.55109
  17. J. Revaud, G. Lavoue, A. Baskurt, "Improving Zernike Moments Comparison for Optimal Similarity and Rotation Angle Retrieval", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 31, No. 4, pp. 627-636, 2009, DOI: 10.1109/TPAMI.2008.115
  18. M. S. Choi, W. Y. Kim, "The description and retrieval of a sequence of moving objects using a shape variation map", Pattern Recognition Letters, Vol. 25, No. 12, pp. 1369-1375, 2004, DOI: 10.1016/j.patrec.2004.05.010
  19. J. M. Lee, W. Y. Kim, "A New Shape Description Method Using Angular Radial Transform", IEICE Transactions on Information and Systems, E95-D(6), pp. 1628-1635, 2012, DOI: 10.1587/transinf.E95.D.1628
  20. B.S. Manjunath, J. R. Ohm, V.V. Vasudevan, A. Yamada, "Color and Texture Descriptors", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 11, No. 6, pp. 703-715, 2001, DOI: 10.1109/76.927424