Automatic Zooming Mechanism for Capturing
Clear Moving Object Image Using HighDefinition Fixed Camera
Hsien-Chou Liao*, Po-Yueh Chen**, Zi-Jun Lin**, Zi-Yi Lim**

Department of Computer Science and Information Engineering, Chaoyang University of Technology,
168, Jifeng E. Rd., Wufeng District, Taichung, 41349 Taiwan, R. O. C.
**
Department of Computer Science and Information Engineering, National Changhua University of Education,
No.1, Jinde Rd., Changhua City, Changhua County, 500 Taiwan, R. O. C.
seafoodliao@gmail.com, pychen@cc.ncue.edu.tw, beiwue2006@gmail.com, joslimzy@gmail.com

Abstract—High definition (HD) camera is widely used in surveillance systems. An HD camera with optical zoom is useful formonitoring a large area. However, it is inconvenient for a user to manually control the optical zoom for a long time. To exploit thefunctionality and extend the application domains of a HD camera, the zooming should be controlled automatically. Therefore, anautomatic zooming mechanism is proposed in this paper. When the number of an object is small in the field of view (FOV) of thecamera and an object is moving through the FOV, the zoom is controlled for capturing the object as clear as possible. A clear object
image is useful for related image-based services, such as face recognition. In order to achieve the above goal, a Gaussian Mixture
Model (GMM), temporal image differencing, a CamShift tracking method, and a Kalman filter are utilized for object detection andtracking. Then, an adaptive neuro-fuzzy inference system (ANFIS) is used to learn and determine a suitable value for adjusting thezoom. According to the experimental study of the prototype, the results show that the proposed mechanism is useful to capture theclear images of moving objects in a practical environment. A face detection algorithm is also used to demonstrate the feasibility of thecaptured clear images.
Keyword—Object tracking, Surveillance system, Intelligent video surveillance, Neural network
Hsien-Chou Liao received the B.S. and Ph.D. degrees in Computer Science and Information Engineering from National ChiaoTung
University in 1991 and 1998, respectively. He is a professor, Department of Computer Science and Information Engineering, atChaoyang University of Technology, Taiwan, R.O.C. He is also a senior member of IEEE. His research interests include location-based
service, smart technology, mobile computing, computer vision, and pattern recognition.

Po-Yueh Chen received his B.S, M.S., and Ph.D. degrees in EE from National Taiwan University in 1988, National Chiao Tung
University in 1990 and University of Maryland at College Park in 1997 respectively. Currently, Dr. Chen is a faculty member in
Department of Computer Science and Information Engineering, National Changhua University of Education, Changhua, Taiwan. His
research interests include image processing, FPGA implementations, VLSI architecture design and digital IC design.

Zi-Jun Lin received the B.S. and M.S. in Computer Science and Information Engineering from the Chaoyang University of Technology
in 2014 and National Changhua University of Education in 2016, respectively. His current research interests are in the computer vision.

Zi-Yi Lim received the B.S. and M.S. in Computer Science and Information Engineering from the Chaoyang University of Technology,Taiwan, Republic of China, in 2014 and 2016. His current research interests are in the area of computer vision.