KEYWORDS: Remote sensing, Data processing, Web services, Image processing, Classification systems, Data modeling, Data storage, Image classification, Image fusion, Process modeling
With the rapid increase of remote-sensing information data, remote-sensing information processing becomes more
important and complicated. However, the processing methods used lead to low processing speed, and make it difficult to
realize resource sharing and mutual operation. Web Services technology can promote research into rapid processing
and share of the remote-sensing data in a heterogeneous environment, so it can help to solve this problem. The existing
problem is that descriptions of the service lack of well-defined semantic information and reasoning ability, so the
computer can't understand the rich information from the network. Based on the situation mentioned above, this article
puts forward a uniform semantic model to solve this kind of problem.
Road extraction plays an important role in many applications such as traffic monitoring. In order to speed the extraction
and enhance its precision, an approach based on particle filtering is proposed in this paper. Firstly, an improved line
detector is presented to extract road candidates, which makes use of the road characteristic on SAR images. Then particle
filtering based on Monte Carlo theory is applied to group the candidates. Applied results show that the road extraction
method is effective and the road features on SAR images have been extracted accurately. Moreover, the method can be
realized simply and save the amount of calculation.
Image registration plays a critically important role in many practical problems in diverse fields. A new object-oriented
image matching algorithm is presented based on the convexity model (CM) and full-scale image segmentation. The core
idea of this matching algorithm is to use image objects as matching unit rather than points or lines. This algorithm firstly
converts images into image objects trees by full-scale segmentation and convexity model restriction. Because image
objects which accord with the convexity model have rich and reliable statistical information and stable shapes, more
characteristics can be used in object-based image matching than pixel-based image matching. Initial experiments show
that matching algorithm proposed in this paper is not sensitive to rotation and resolution distortion, which can
accomplish the image matching and registration automatically.
With the development of hydrographical work and information techniques, digital charts are more and more popular in
maritime applications, and an embedded product--PDA (personal digital assistant) is widely used in navigation for its
smallness and portability. However, there is lack of PDA-based product which can provide integrated data management,
real-time alternate display and ship auto-track application based on traditional paper chart and s-57 ENC. Aiming at this,
some new techniques and algorithms including integrated spatial data management and display mode for ENC and paper
chart, multi-scale data organization, embedded chart navigation method based on GPS are presented. And the integrated
electronic chart pocket navigator system (PNS) based on PDA was developed.
KEYWORDS: Personal digital assistants, Navigation systems, Data modeling, Data storage, Data integration, Binary data, Safety, Oceanography, Geographic information systems, Algorithm development
PDA (Personal Digital Assistant) is a useful tool for navigation which has many advantages such as its smallness and
portability. In the meantime, digital charts have been found a wide application in past ten years, and many users are
hoping for giving up the paper chart entirely and using ENC by the law. However, traditional paper chart is a nonreplaced
tool for people in hydrographical survey and other application fields, and would coexist with ENC for a long
time. How to manage and display integrated chart for traditional paper chart and ENC together in PDA for navigating is
still an unsolved problem. Aiming at this, a new integrated spatial data model and display techniques for ENC and paper
chart are presented. The core idea of the new algorithm is to build an integrated spatial data model, structure and display
environment for both paper chart and ENC. Based on the above algorithms and strategies, an Integrated Electronic Chart
Pocket Navigator System named PNS based on PDA was developed. It has been applied in Tianjin Marine Safety
Administration Bureau and obtained a good evaluation.
The key operation in airports extraction from remote sensing images is to extract the airport edges and obtain their
approximate strait lines. For example, the Canny can be used to extract image edges and the result edges can be used to
obtain approximate strait lines by Hough Transform or other strait line fitting methods. However, background of airport
target is so complex that large numbers of useless edge pixels will be extracted from surroundings by Canny algorithm
and those disheveled edge pixels will interfere with the following analysis. For example, it is difficult to use Hough
Transform to extract useful strait lines of airport edges from the binary image composed of airport edges and other
useless edge pixels because the proportion of disheveled edges is far larger than the one of airport edges. One solution is
to smooth the image before edges detection. Unfortunately, most of image smoothing operation cannot weaken useless
edges effectively. Moreover, it will also damage the useful ones and makes it more difficult to extract useful strait lines.
Though some edge-preserve smoothing algorithms have been proposed, it is still difficult to solve this problem because
too many disheveled but robust edges will be preserved together. In this paper, a novel edge-preserve image smoothing
algorithm based on Convexity Model is discussed with its practical application in airport extraction. This smoothing
algorithm will whittle or restrain those regions whose features accord with the Convexity Model and whose sizes are
smaller than the specified one. The experimental results show that the algorithm is effective in removing noises and
small regions with few influences on those edges of interested targets whose scales are larger than the specified one. The
practical applications show that this smoothing algorithm can increase the efficiency and precision of airports extraction.
Maritime Search and Rescue (SAR) is the fast, systematical and efficient operations to rescue persons in maritime distress at sea and control the spread of distress incident. This paper introduces an intelligent maritime search and rescue directing system built by Tianjin Maritime Safety Administration. It is an intelligent assistant tool used in the operation of maritime search and rescue. It integrates five subsystems - marine communication system, vessel monitoring system, intelligent decision assistant system, on-scene information collecting system, and remote directing system. It is a representative application system of Locate Based Service. This system is successfully applied in Tianjin Maritime Safety Administration and China 2006's BoHai Sea Search and Rescue.
KEYWORDS: Databases, Data modeling, Visualization, Electronic components, System integration, Oceanography, Data storage, Human-machine interfaces, Data conversion, Associative arrays
In recent years with the fast development of electronic charts marking, how to design and implement a flexible and complete marking system on electronic chart is very important and urgent. Aiming at the shortcomings of existent chart marking system, this paper provides a good solution and implements an electronic chart marking system. Firstly the design concepts and framework of the marking system are introduced. Then several kinds of key techniques including drawing of the chart marks, organization and management of marking data, integration of marking system and other electronic chart system are described in detail. Based on the above theories and methods, a system named HYECMS is developed and obtained application in Tianjin Marine Bureau.
Automatic extracting and updating road networks is a key work for updating geo-spatial information especially in developing countries. Aiming at the deficiency of the perceptual grouping based on geometric relation and based on the similar relation, a new perceptual grouping method that is so-called the perceptual grouping based on teh whole relationship is presented. In this method, all kinds of information including geometric properties, image attributes and other information are group based on the similarity rules. Based on this new grouping framework, the principles and the procedures of automatic road segments grouping are described in detail from two aspects: one is automatic perceptual grouping for similar road segments and another is automatic extended road segments for no-similar road segments. At last some discussion for new perceptual grouping strategy is given.
Automatic extracting and updating road networks is a key work for updating geo-spatial information especially in developing countries. In this paper, a whole framework for automatic road extraction is presented firstly. Then the strategy and algorithms using GIS data for road extraction are discussed. A hybrid method based on structure information and statistical information for road extraction is emphasized in this paper. Different extraction strategy and grouping techniques are employed for different extracting methods. Because of the importance of structure information in road extraction, the extraction of candidate road segments based on structure information is described. For road extraction from images with different resolution based on structure information, different grouping technique is applied. The grouping technique based on whole relation and the grouping technique based on new profile tracing algorithm is separately employed for images with low resolution and with high resolution. The road extraction based on statistical information is the supplement of structure information. A new statistical model is presented and the candidate road-tracing algorithm based on adaptive template is discussed. And the grouping based on ribbon-snake model is briefly introduced. Automatic road recognition is a necessary task for automatic extracting road networks. So aiming at this we put all kinds of road recognition knowledge into the knowledge base and build a road recognition expert system. The fuzzy theory is applied for representing road models and road knowledge reasoning. The strategy for using global information to guide the further road extraction is presented. At last some examples and the summary are given.
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