Occlusion Tolerant Object Recognition Methods for Video Surveillance and Tracking of Moving Civilian Vehicles

Recently, there is a great interest in moving object tracking in the fields of security and surveillance. Object recognition under partial occlusion is the core of any object tracking system. This thesis presents an automatic and real-time color object-recognition system which is not only robust but also occlusion tolerant. The intended use of the system is to recognize and track external vehicles entered inside a secured area like a school campus or any army base. Statistical morphological skeleton is used to represent the visible shape of the vehicle. Simple curve matching and different feature based matching techniques are used to recognize the segmented vehicle. Features of the vehicle are extracted upon entering the secured area. The vehicle is recognized from either a digital video frame or a static digital image when needed. The recognition engine will help the design of a high performance tracking system meant for remote video surveillance.

Grantor dc:publisher

University of North Texas

Year dc:date

2007

Author dc:creator

• Pati, Nishikanta

Contributors dc:contributor

• Guturu, Parthasarathy
• Mohanty, Saraju P.
• Buckles, Bill P., 1942-
• Yuan, Xiaohui

• object recognition
• tracking
• video object segmentation
• curve matching
• Electronic surveillance.
• Television in security systems.
• Security systems.
• Computer vision.
• Pattern recognition systems.
• Image processing.

Statement dc:rights

• Public
• Copyright
• Pati, Nishikanta
• Copyright is held by the author, unless otherwise noted. All rights reserved.

Language dc:language

English

Identifier

oclc: 227206270
https://digital.library.unt.edu/ark:/67531/metadc5133/
ark: ark:/67531/metadc5133

OAI identifier oai:identifier

info:ark/67531/metadc5133