IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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Depth Image Based Feature Detection Method Using Hybrid Filter

융합형 필터를 이용한 깊이 영상 기반 특징점 검출 기법

  • Received : 2017.09.07
  • Accepted : 2017.11.02
  • Published : 2017.12.31
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Abstract

Image processing for object detection and identification has been studied for supply chain management application with various approaches. Among them, feature pointed detection algorithm is used to track an object or to recognize a position in automated supply chain systems and a depth image based feature point detection is recently highlighted in the application. The result of feature point detection is easily influenced by image noise. Also, the depth image has noise itself and it also affects to the accuracy of the detection results. In order to solve these problems, we propose a novel hybrid filtering mechanism for depth image based feature point detection, it shows better performance compared with conventional hybrid filtering mechanism.

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References

  1. D.H. Jeong, J.I. Park, Y.T. Kim, "Study on Design of Mobile Robot for Autonomous Freight Transportation," Journal of Korean Institute of Intelligent, 2013 (in Korean).
  2. S. Song, J. Xiao, "Sliding Shapes for 3D Object Detection in Depth Images," Proceedings of Springer Conference on Computer Vision, pp. 634-651, 2014.
  3. J. Salas, C. Tomasi, "People Detection Using Color and Depth Images," Proceedings of Springer Conference on Pattern Recognition, pp. 127-135, 2011.
  4. L. Bo, X. Ren, D. Fox, "Depth Kernel Descriptors for Object Recognition," Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 821-826, 2011.
  5. T.D. Duan, D.A. Duc, T.L.H. Du, "Combining Hough Transform and Contour Algorithm for Detecting Vehicles' License-Plates," Proceedings of IEEE International Symposium on Intelligent Multimedia, Video and Speech Processing, pp. 747-750, 2004.
  6. J.H. Oh, C.S. Jeong, "Comparison Between DSC and Previous Algorithms for Edge Detection," Korea Information Science Society, Vol. 31, No. 1, pp. 739-741, 2004 (in Korean).
  7. G. Saygili, L. van der Maaten, E. A. Hendriks, "Hybrid Kinect Depth Map Refinement for Transparent Objects," Proceedings of IEEE International Conference on Pattern Recognition, pp. 2751-2756, 2014.
  8. S. Gupta, R. Girshick, P. Arbelaez, J. Malik, "Learning Rich Features From RGB-D Images for Object Detection and Segmentation," Proceedings of Springer Conference on Computer Vision, pp. 345-360, 2014.
  9. I.S. Hwang, I.K. Eom, Y.H. Moon, S.W. Ha, "A Fast Interest Point Detection Method in SURF Algorithm," IEMEK J. Embed. Sys. Appl., 2015 (in Korean)
  10. J.H. Lee, Y.H. Lee, E.Y. Cha, "A Study of Face Feature Tracking and Moving Measure Devices," IEMEK J. Embed. Sys. Appl., 2011 (in Korean).
  11. E. Rosten, T. Drummond, "Machine Learning for High-speed Corner Detection," Proceedings of Springer Conference on Computer Vision, pp. 430-443, 2006.
  12. D.G. Lowe, "Distinctive Image Features From Scale-Invariant Keypoints," International journal of computer vision, Vol. 60, No. 2, 2004.
  13. E. Mair, G.D. Hager, D. Burschka, M. Suppa, G. Hirzinger, "Adaptive and Generic Corner Detection Based on the Accelerated Segment Test," Proceedings of Springer Conference on Computer vision, pp. 183-196, 2010.
  14. H. Bay, T. Tuytelaars, L. Van Gool, "Surf: Speeded up Robust Features," Proceedings of Springer Computer vision, pp. 404-417, 2006.
  15. M. Calonder, V. Lepetit, C. Strecha, P. Fua, "Brief: Binary Robust Independent Elementary Features," Proceedings of Springer Conference on Computer vision, pp. 778-792, 2010.
  16. M.S. Arulampalam, S. Maskell, N. Gordon, T. Clapp, “A Tutorial on Particle Filters for Online Nonlinear/non-Gaussian Bayesian Tracking,” IEEE Transactions on signal processing, Vol. 50, No. 2, pp. 174-188, 2002. https://doi.org/10.1109/78.978374
  17. M. Lakshmanna, A. Maheswari, “Modified Classical Unsharp Masking Algorithm,” Proceedings of International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, No. 9, pp. 271-276, 2013.
  18. W. Gao, X. Zhang, L. Yang, H. Liu, "An Improved Sobel Edge Detection," Proceedings of IEEE International Conference on Computer Science and Information Technology, Vol. 5, pp. 67-71, 2010.
  19. R. Srivastava, J.R.P. Gupta, H. Parthasarthy, S. Srivastava, "PDE Based Unsharp Masking, Crispening and High Boost Filtering of Digital Images," Proceedings of Springer Conference on Contemporary computing, pp. 8-13, 2009.