INFORMATION CHANGE THE WORLD

International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.7, No.12, Nov. 2015

Face Detection and Auto Positioning for Robotic Vision System

Full Text (PDF, 618KB), PP.1-9


Views:70   Downloads:1

Author(s)

Muralindran Mariappan, Tan Wei Fang, Manimehala Nadarajan, Norfarariyanti Parimon

Index Terms

Face detection;auto positioning;skin colour segmentation;servo motor

Abstract

Robotic vision system has taken a great leap in the field of robotics. Vision system is an essential tool to be implemented in a robot for visual communication between robot and human especially in the application of Tele-Diagnostic Robot. The robot vision system must always be in the field of view. The ability for the vision system to automatically track the person in communication is crucial for the remote medical specialist. To circumvent this problem, a face detection technique is implemented and it is performed using skin color segmentation with two color space which are YCbCr and HSV. Besides that, morphological operations are also done to detect the face region accurately. Two DOF servo mechanism were designed to ensure that the servo motor rotates to centralize the detected face region. A real-time testing were conducted and it was found that this system results a good performance.

Cite This Paper

Muralindran Mariappan, Tan Wei Fang, Manimehala Nadarajan, Norfarariyanti Parimon,"Face Detection and Auto Positioning for Robotic Vision System ", IJIGSP, vol.7, no.12, pp.1-9, 2015.DOI: 10.5815/ijigsp.2015.12.01

Reference

[1]Down, M.P and Sands, R.J. Biometrics: An Overview of the Technology, Challenges and Control Considerations. Information Systems Control Journal, Volume 4, 2004.

[2]http://www.irobot.com/us/learn/commercial.aspx.

[3]Luo, R.C., Chen, C., and Pu, Y. Internet Based Remote Supervisory System for Tele-medicine Robot Application. IEEE Workshop on Advances Robotics and its Social Impact, 2009, 153-158.

[4]Muralindran Mariappan, Vigneswaran Ramu, Brendan K.T.T, Thayabaren Ganesan, Manimehala Nadarajan. Design and Development of Communication and Control Platform for Medical Tele-diagnosis Robot (MTR). International Journal of Networks and Communications, 2013, 3(1): 12-20.

[5]Mohamed, A.S.S., Weng, Y., Ipson, S.S., Jiang, J. Face Detection based on Skin Colour in Image by Neural Networks. International Conference on Intelligent and Advanced System, 2007, 779-783.

[6]Kovac J, Peer P, Solina F. Human skin color clustering for face detection. In: IEEE Region 8 International Conference on Computer as a Tool, 2003, pp. 144 –148. 

[7]Shahrel A Suandi, Shuichi Enokida, Toshiaki Ejima. EMo Tracker: Eyes and Mouth Tracker. Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing, IAPR Sponsored Conference, India, Kolkata, 2004, pp. 269-274. 

[8]Zaher Hamid Al-Tairi, Rahmita Wirza Rahmat, M. Iqbal Saripan, and Puteri Suhaiza Sulaiman. Skin Segmentation Using YUV and RGB Color Spaces. Journal of Information Processing Systems, 2013, 10(2): 283-299.

[9]Bojic. N and K. K. Pang. Adaptive skin segmentation for head and shoulder video sequence. SPIE Visual Communication and Image Processing. Australia: Perth, 2000.

[10]Kukharev G. and A. Nowosielski. Visitor identification elaborating real time face recognition system. In Proc. 12. 2014.

[11]Chai and Ngan. Face segmentation using skin-color map in videophone applications. IEEE Trans. on Circuits and Systems for Video Technology, 1999, 9(4): 551-564.

[12]Jorge Alberto Marcial Basilio, Gualberto Aguilar Torres, Gabriel Sanchez Perez, L. Karina Toscano Medina and Hector M. Perez Meana. Explicit Image Detection using YCbCr Space Color Model as Skin Detection. Applications of Mathematics and Computer Engineering, 2010, pp 124-128.

[13]Singh, S., Cauhan, D.S., Vasta, M. and Singh, R. A Robust Skin Color Based Detection Algorithm, Tamkang Journal of Science and Engineering, Volume 6, Issue 4, 2003, 227-234.

[14]Muralindran Mariappan, Manimehala Nadarajan, Rosalyn R. Porle, Vigneswaran Ramu and Brendan Khoo, A LabVIEW Design for Frontal and Non- Frontal Human Face Detection System in Complex Background, Applied Mechanics and Materials, Volume 490-491, 1259-1266, 2014.

[15]Fan Hai Xiang and Shahrel Azmin Suandi. Fusion of Multi Color Space for Human Skin Region Segmentation. International Journal of Information and Electronics Engineering, March 2013, 3(2):172-174.

[16]Sayantan Thakur, Sayantanu Paul, Ankur Mondal. Face Detection Using Skin Tone Segmentation. 2011 World Congress on Information and Communication Technologies, 2011, pp. 53-60.

[17]Rafel C. Gonzalez, Richard E Woods. Digital Image processing (Second edition). Prentice Hall, 2002.

[18]Bernhard Froba and Christian Kublbeck2001. Real-Time Face Detection Using Edge-Orientation Matching. 3rd International Conference on Audio and Video Based Biometric Person Authentication, 2001, pp78-83.

[19]Li Bai and LinLin Shen. Face Detection by Orientation Map Matching. International Conference on Computational Intelligence for Modelling Control and Automation, Austria, Feb 2003.

[20]Linlin Shen and Li Bai. Face Detection in Grey Images Using Orientation Matching. School of Computer Science & IT University of Nottingham. Proceeding 17th European Simulation Multiconference, 2003.

[21]Viola P. and M. Jones. Rapid Object Detection using a Boosted Cascade of Simple Features. IEEE Conf. on Computer Vision and Pattern Recognition, 2001, Kauai, Hawaii.

[22]Rainer Lienhart and Jochen Maydt. An Extended Set of Haar-like Features for Rapid Object Detection, 2002, IEEE ICIP. 1:900-903.

[23]Qiao R.Y and Y.Guo. Face Detection Using Soft Margin Boosting. Image and Vision Comuting. New Zealand Conference, 2002, pp.157-161.

[24]Roland T. Chin and Charles R. Dyer. Model-Base Recognition in Robot Vision. Computing Surveys, March 1986, 18(1): 67- 108.

[25]Marius Bulacu, Nobuo Ezaki and Lambert Schomaker. Text Detection and Pose Estimation for a Reading Robot. Mobile Robots Motion Planning, New Challenges, pp.39-62.

[26]Kazuhiro Fukui and Osamu Yamaguchi. Face Recognition Using Multi-viewpoint Patterns for Robot Vision. 11th International Symposium of Robotics Research, 2003, pp.192-201.

[27]Guha Balakrishnan, Fredo Durand and John Guttag. Detecting Pulse from Head Motions in Video. IEEE Conference on Computer Vision and Pattern Recognition, 2013, pp 3430 – 3437.

[28]Masakazu Matsugu, Kan Torii, Yoshinori Ito, Tadashi Hayashi and Tsutomu Osaka, Face Tracking Active Vision System with Saccadic and Smooth Pursuit, IEEE Conference on Robotics and Biomimetics, China, 2006, pp 1322- 1328.

[29]Yuji Nishina, Joo Kooi Tan, Hyoung Seop Kim and Seiji Ishikawa, Development of Autonomous Robot for Face Tracking, International Conference on Control, Automation and Systems, Seoul, 2007, pp 1178-1181.

[30]Hao-Yu Wu, Michael Rubinstein, Eugene Shih, John Guttag, Fredo Durand and William Freeman. Eulerian Video Magnification for Revealing Subtle Changes in the World. Medical Measurements and Applications (MeMeA), 2014 IEEE International Symposium on, 2012, pp 1-4.

[31]Thu-Thao Nguyen. Real-Time Face Detection and Tracking. School of Electrical and Computer Engineering of Cornell University, December 2012.