Subscribe Now Subscribe Today
Research Article

Study on an Intelligent Human Detection System for Unmanned Area Security in Ports

Mi Chao, Huang Youfang, Liu Haiwei, He Xin and Mi Weijian
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

This study purposes an intelligent human detection system based on video cameras for unmanned area security in ports. The optimized Histograms of Oriented Gradients (HOG) descriptors are used to preprocess the image and the HOG features are then built. And then, a Support Vector Machine (SVM) classifier is applied to process those HOG features and determine whether there are humans in the image. At last, this paper describes a group of experiments of human detection in Coal Terminal of Tianjin Port. The result shows that the computer takes 500 m sec to analyze a 720p image and detect the human and the correctness is 94% which meets the requirements of the unmanned area security in ports.

Related Articles in ASCI
Similar Articles in this Journal
Search in Google Scholar
View Citation
Report Citation

  How to cite this article:

Mi Chao, Huang Youfang, Liu Haiwei, He Xin and Mi Weijian, 2013. Study on an Intelligent Human Detection System for Unmanned Area Security in Ports. Journal of Applied Sciences, 13: 3221-3226.

DOI: 10.3923/jas.2013.3221.3226


1:  Mueen, A., M.S. Baba and R. Zainuddin, 2007. Multilevel feature extraction and X-ray image classification. J. Applied Sci., 7: 1224-1229.
CrossRef  |  Direct Link  |  

2:  Bouchrika, I. and M.S. Nixon, 2006. People detection and recognition using gait for automated visual surveillance. Proceedings of the IEE International Symposium on Imaging for Crime Detection and Prevention, June 13-14 2006, London, pp: 576-581.

3:  Chan, A.L., 2011. Multi-stage infrared stationary human detection. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, May 22-27, 2011, Prague, pp: 1221-1224.

4:  Chand, P., A. Davari, B. Liu and K. Sedghisigarchi, 2007. Feature extraction of power quality disturbances using adaptive harmonic wavelet transform. Proceedings of the 39th Southeastern Symposium on System Theory, March 4-6, 2007, Macon, GA., pp: 266-269.

5:  Li, C., L. Guo and Y. Hu, 2010. A new method combining HOG and Kalman filter for video-based human detection and tracking. Proceedings of the 3rd International Congress on Image and Signal Processing, October 16-18, 2010, Yantai, pp: 290-293.

6:  Loum, G., C.T. Haba, J. Lemoine and P. Provent, 2007. Texture characterisation and classification using full wavelet decomposition. J. Applied Sci., 7: 1566-1573.
CrossRef  |  Direct Link  |  

7:  Jung, H., J.K. Tan, S. Ishikawa and T. Morie, 2011. Applying HOG feature to the detection and tracking of a human on a bicycle. Proceedings of the 11th International Conference on Control, Automation and Systems, October 26-29, 2011, Gyeonggi-do, pp: 1740-1743.

8:  Lee, K., C.Y. Choo, H.Q. See, Z.J. Tan and Y. Lee, 2010. Human detection using histogram of oriented gradients and human body ratio estimation. Proceedings of the 3rd IEEE International Conference on Computer Science and Information Technology, Volume 4, July 9-11, 2010, Chengdu, pp: 18-22.

9:  Dalal, N. and B. Triggs, 2005. Histograms of oriented gradients for human detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1, June 20-26, 2005, San Diego, CA., USA., pp: 886-893.

10:  Yang, T., F. Chen, D. Kimber and J. Vaughan, 2007. Robust people detection and tracking in a muti-camera indoor visual surveillance system. Proceedings of the IEEE International Conference on Multimedia and Expo, July 2-5, 2007, Beijing, pp: 675-678.

11:  Senst, T., R.H. Evangelio and T. Sikora, 2011. Detecting people carrying objects based on an optical flow motion model. Proceedings of the IEEE Workshop on Applications of Computer Vision, January 5-7, 2011, Kona, HI., pp: 301-306.

12:  Fan, X., L. Xu, X. Zhang and L. Chen, 2008. The research and application of human detection based on support vector machine using in intelligent video surveillance system. Proceedings of the 4th International Conference on Natural Computation, October 18-20, 2008, Jinan, pp: 139-143.

13:  Yamashita, A., Y. Ito, T. Kaneko and H. Asama, 2011. Human tracking with multiple cameras based on face detection and mean shift. Proceedings of the IEEE International Conference on Robotics and Biomimetics, December 7-11, 2011, Karon Beach, Phuket, pp: 1664-1671.

14:  Pang, Y.W., Y. Yuan, X.L. Li and J. Pan, 2011. Efficient HOG human detection. Signal Process., 91: 773-781.
CrossRef  |  Direct Link  |  

©  2021 Science Alert. All Rights Reserved