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Maritime Objects Recognition and Tracking Based on Shape Appearance
Author: WangMingFen
Tutor: LiCuiHua
School: Xiamen University
Course: Applied Computer Technology
Keywords: SUSAN operator shape context two-stage recursive
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 122
Quote: 2
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Abstract
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Maritime objects detection、recognition and Tracking technologies are very useful in many areas, such as coastal defense、customs management、marine anti-smuggling、port scheduling and other occasions. Early warning、alarm of sea collision between vessels and identify the types of moving targets in the sea, all of these have important application.This thesis presents a method of ship identification and tracking technology. First, it describes current development status of maritime moving target detection and tracking research ,then outlines some methods of ships identification and tracking; We carry up a deep research into the ship recognition based on the shape feature matching and track the ship by CamShift algorithm. The main research innovations and contributions are summarized as follows:1、The paper proposes an adaptive threshold of SUSAN method. Threshold is calculated in every single SUSAN template, which makes it overcome the dissatisfactory results of traditional SUSAN operator.2、We carry up a deep research into shape feature matching. Shape context is used to describe shape points. Then a two-stage recursive algorithm for recognition is proposed. At rough matching stage, shape distance is used to describe similarity of two targets and quickly construct a small set of candidate targets. At detail matching stage, we implement it using iteration of correspondence through shape context matching and deformation using TPS model.3、We explore the CamShift algorithm and put it into the ship tracking system. We build the hue histogram on the identified ship region and then track it using the CamShift algorithm in the following frames. And the CamShift algorithm can be applied to track multiple ships simultaneously.
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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