Identifying images on moving objects to enhance the recognition

  • Authors

    • C. Raghavendra
    • A. Kumaravel
    • S. Sivasubramanian
    2017-12-31
    https://doi.org/10.14419/ijet.v7i1.5.9162
  • Abstract

    To explore another group of algorithms that break down time-changing scenes, perceiving and following educated questions after some time. The new procedures are wanted to address key request of moving pictures, including capricious moment to-minute changes in region, gauge, presentation, lighting, and obstacle. We exhibit a novel endeavour in which objects turn and divert while suspended from a flexible's arms;the identification and following calculation joins attributes of various earlier distributed strategies, consolidating them in a novel mould to empower this recently presented assignment. Different strategies have discovered that enhancing recognition will enhance following; we demonstrate that enhanced following enhances object recognition.

  • References

    1. [1] W.C., Gelfand, Ta D.N., Pulli K, and Chen N. SURFTrac: Efficient Tracking and Continuous Object Recognition Using Local Feature Descriptors. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (2009), 2937-2944.

      [2] Foresti G.L.: Object Recognition and Tracking for Remote Video Surveillance. IEEE Transactions on Circuits and Systems for Video Technology, 9 (7), (1999).

      [3] C. Raghavendra, Dr. A Kumaravel, A. Anjaiah, “A New Hybrid Method for Image De-Noising In Light Of Wavelet Transformâ€, International Journal of Pure and Applied Mathematics, Volume 116 No. 21 2017, 197-202.

      [4] K. Rajendra Prasad, C. Raghavendra, K Sai Saranya, “A Review on Classification of Breast Cancer Detection using Combination of The Feature Extraction Modelsâ€, International Journal of Pure and Applied Mathematics, Volume 116 No. 21 2017, 203-208.

      [5] Mikolajczyk K. and Schmid C.: Performance Evaluation of Local Descriptors. IEEE Transactions on Pattern Analysis & Machine Intelligence, 27(10), (2005), 1615–1630,

      [6] P. Kiran Kumar, C. Raghavendra, Dr. S. Sivasubramanyan, Exploring Multi Scale Mathematical Morphology for Dark Image Enhancement, International Journal of Pharmacy and Technology, Dec-2016, Vol. 8, Issue No.4, 23590-23597.

      [7] Grauman K. and Darrell T.: The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features. Proceedings of IEEE International Conference on Computer Vision, 2, (2005), 1458–1465.

      [8] C. Raghavendra, A. Kumaravel and S. Sivasuramanyan, “Features Subset Selection using Improved Teaching Learning based Optimisation (ITLBO) Algorithms for Iris Recognitionâ€, Indian Journal of Science and Technology, Vol 10(34), DOI: 10.17485/ijst/2017/v10i34/118307, September 2017.

      [9] K. Rajendra Prasad, C. Raghavendra, Effective Mammogram Classification Using Various Texture Features, Journal of Advanced Research in Dynamical and Control Systems, Vol. 9. Sp– 12 / 2017.

      [10] Yuen J., TorralbaA.,Liu C., Sivic J., and Freeman W.T.: SIFT Flow: Dense Correspondence Across Different Scenes. In ECCV '08: Proceedings of the 10th European Conference on Computer Vision, (2008), 28-42.

      [11] C. Nalini, C. Raghavendra, K. Rajendra Prasad, “Comparative Observation and Performance Analysis of Multiple Algorithms on Iris Dataâ€, International Journal of Pure and Applied Mathematics, Volume 116 No. 9 2017, 319-325.

      [12] Wagner D., Reitmayr G., Mulloni A., Drummond T., and Schmalstieg D.: Pose Tracking from Natural Features on Mobile Phones. In ISMAR '08: Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality, (2008), 125-134.

      [13] K. Rajendra Prasad, C. Raghavendra, Padakandla Vyshnav, “Intelligent System for Visualized Data Analytics A Reviewâ€, International Journal of Pure and Applied Mathematics, Volume 116 No. 21 2017, 217-224.

      [14] Lowe D.: Local Feature View Clustering for 3D Object Recognition. In 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01), 1, (2001), 682-688.

      [15] Ruiz-del-Solar J and Loncomilla P. Gaze Direction Determination of Opponents and Teammates in Robot Soccer. Lecture Notes in Computer Science, 4020, (2006), 230–242.

      [16] Ruiz-del-Solar J. and Loncomilla P. A Fast Probabilistic Model for Hypothesis Rejection in SIFT Based Object Recognition. Lecture Notes in Computer Science, 4225, (2006), 696–705.

      [17] Loncomilla P. & Ruiz-del-Solar J.: Robust Object Recognition Using Wide Baseline Matching for RoboCup Applications. Lecture Notes in Computer Science, 5001, (2008), 441–448.

      [18] C. Raghavendra, A. Kumaravel, S. Sivasubramanian, “Iris Technology: A Review on Iris Based BiometricSystems for Unique Human Identificationâ€, International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies – 2017, association WithIEEE.

      [19] Mikolajczyk K., Tuytelaars T., Schmid C., Zisserman A., Matas J., Schaffalitzky F., Kadir T., and Van Gool L.: A Comparison of Affine Region Detectors. International Journal of Computer Vision 65(1), (2005), 43–72.

      [20] Granger R.: Engines of the Brain: The Computational Instruction Set of Human Cognition. In AI Magazine, 27, (2006), 15-32.

      [21] http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/

      [22] T. Padmapriya and V. Saminadan, “Improving Throughput for Downlink Multi user MIMO-LTE Advanced Networks using SINR approximation and Hierarchical CSI feedbackâ€, International Journal of Mobile Design Network and Innovation- Inderscience Publisher, ISSN : 1744-2850 vol. 6, no.1, pp. 14-23, May 2015.

      [23] S.V.Manikanthan and K.srividhya "An Android based secure access control using ARM and cloud computing", Published in: Electronics and Communication Systems (ICECS), 2015 2nd International Conference on 26-27 Feb. 2015,Publisher: IEEE,DOI: 10.1109/ECS.2015.7124833.

      [24] Rajesh, M., and J. M. Gnanasekar. "Path observation-based physical routing protocol for wireless ad hoc networks." International Journal of Wireless and Mobile Computing 11.3 (2016): 244-257.

  • Downloads

  • How to Cite

    Raghavendra, C., Kumaravel, A., & Sivasubramanian, S. (2017). Identifying images on moving objects to enhance the recognition. International Journal of Engineering & Technology, 7(1.5), 279-282. https://doi.org/10.14419/ijet.v7i1.5.9162

    Received date: 2018-01-11

    Accepted date: 2018-01-11

    Published date: 2017-12-31