Opponent colour median-based scale invariant local ternary pattern: a new feature descriptor for moving object detection

ABSTRACT

This article presents a new colour-texture feature descriptor called opponent colour median-based scale invariant local ternary pattern (OCMD-SILTP) to deal with dynamic backgrounds, similar texture regions, moving cast shadow, and illumination changes. Here, the incoming image frames are first divided into several sub regions and then the colour-texture features are derived by applying OCMD-SILTP on the individual colour planes (R, G, and B) as well as opponent colour planes (R-G, R-B, and G-B). For opponent planes, the median of neighbourhood pixels of one color plane is used for thresholding the neighbourhood pixels of opponent color plane. Because of this, the proposed OCMD-SILTP colour-texture descriptors are more immune to scaling and video noises. The background changes are dynamically updated through OCMD-SILTP texture patterns using histogram intersection method. Experiments on publically available dataset prove the significance of proposed approach under complex environments.

KEYWORDS:

• Object detection
• colour
• texture
• dynamic background
• OCMD-SILTP
• surveillance
• tracking
• feature descriptor

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

K. Kalirajan

K. Kalirajan received his Ph.D. degree in Image and Video Processing from Anna University, Chennai (2017) and M.E. degree in VLSI Design from Anna University of Technology, Coimbatore, Tamil Nadu (2009). He obtained his B.E. degree in Electronics and Communication Engineering from Manonmanium Sundaranar University in the year 2003. He is currently working as a Professor in the department of Electronics and Communication Engineering at KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu. He is having 19 years of teaching experience including 5 years of research experience. He is a recognized supervisor at Anna University, Chennai and presently he is guiding 5 research scholars in different research domains such as Computer vision, image and video processing, VLSI design and Deep learning. He has published 14 research articles in various SCI/Scopus indexed international journals. Google scholar: https://scholar.google.com/citations?user=olMVlhIAAAAJ&hl=en

K. Balaji received his M.E., in Network Engineering from Anna University of Technology, Coimbatore, Tamil Nadu (2011). He obtained his B.E. degree in Computer Science and Engineering from Maharaja Engineering College, Coimbatore (2008). He is currently working as an Assistant Professor in the Department of Artificial Intelligence and Data Science, at Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu. He is having 12 years of teaching experience. His research interest includes image processing, Wireless Sensor Network and Big Data. For his credentials, he published more than 10 papers in refereed Scopus indexed international journals and 12 papers in national and international conferences. Email id: [email protected]. Google scholar: https://scholar.google.com/citations?user=OyqVXCoAAAAJ