An object‐oriented methodology to detect oil spills

A new automated methodology for oil spill detection is presented, by which full synthetic aperture radar (SAR) high‐resolution image scenes can be processed. The methodology relies on the object‐oriented approach and profits from image segmentation techniques to detected dark formations. The detection of dark formations is based on a threshold definition that is fully adaptive to local contrast and brightness of large image segments. For the detection process, two empirical formulas are developed that also permit the classification of oil spills according to their brightness. A fuzzy classification method is used to classify dark formations as oil spills or look‐alikes. Dark formations are not isolated and features of both dark areas and sea environment are considered. Various sea environments that affect oil spill shape and boundaries are grouped in two knowledge bases, used for the classification of dark formations. The accuracy of the method for the 12 SAR images used is 99.5% for the class of oil spills, and 98.8% for that of look‐alikes. Fresh oil spills, fresh spills affected by natural phenomena, oil spills without clear stripping, small linear oil spills, oil spills with broken parts and amorphous oil spills can be successfully detected.     

An object‐oriented approach for analysing and characterizing urban landscape at the parcel level

This paper presents an object‐oriented approach for analysing and characterizing the urban landscape structure at the parcel level using high‐resolution digital aerial imagery and LIght Detection and Ranging (LIDAR) data. Additional spatial datasets including property parcel boundaries and building footprints were used to both facilitate object segmentation and obtain greater classification accuracy. The study area is the Gwynns Falls watershed, which includes portions of Baltimore City and Baltimore County, MD. A three‐level hierarchical network of image objects was generated, and objects were classified. At the two lower levels, objects were classified into five classes, building, pavement, bare soil, fine textured vegetation and coarse textured vegetation, respectively. The object‐oriented classification approach proved to be effective for urban land cover classification. The overall accuracy of the classification was 92.3%, and the overall Kappa statistic was 0.899. Land cover proportions as well as vegetation characteristics were then summarized by property parcel. This exercise resulted in a knowledge base of rules for urban land cover classification, which could potentially be applied to other urban areas.     

Design of computer‐based information systems for the Greek local government

A new centrally‐planned approach for the development of computer‐based information systems required by the Greek government is proposed. The overall structure and the technical characteristics of the new Greek local government information system at national level is outlined. A methodology is also proposed for the identification of the hardware and software needs of the individual local authorities and for the development of the necessary software.     

Textural and local spatial statistics for the object‐oriented classification of urban areas using high resolution imagery

Textural and local spatial statistical information is important in the classification of urban areas using very high resolution imagery. This paper describes the utility of textural and local spatial statistics for the improvement of object‐oriented classification for QuickBird imagery. All textural/spatial bands were used as additional bands in the supervised object‐oriented classification. The texture analysis is based on two levels: segmented image objects and moving windows across the whole image. In the texture analysis over image objects, the angular second moment textural feature at a 45° angle showed an improved classification performance with regard to buildings, depicting the patterns of buildings better than any other directions. The texture analysis based on moving windows across the whole image was conducted with various window sizes (from 3×3 to 13×13), and four grey‐level co‐occurrence matrix (GLCM) textural features (homogeneity, contrast, angular second moment, and entropy) were calculated. The contrast feature with the 7×7 window size improved classification up to 6%. One type of local spatial statistics, Moran's I feature with the vertical neighbourhood rule, improved the classification accuracy even further, up to 7%. Comparison of results between spectral and spectral+textural/spatial information indicated that textural and spatial information can be used to improve the object‐oriented classification of urban areas using very high resolution imagery.     

Fuzzy segmentation for object‐based image classification

This Letter proposes an object‐based image classification procedure which is based on fuzzy image‐regions instead of crisp image‐objects. The approach has three stages: (a) fuzzification in which fuzzy image‐regions are developed, resulting in a set of images whose digital values express the degree of membership of each pixel to target land‐cover classes; (b) feature analysis in which contextual properties of fuzzy image‐regions are quantified; and (c) defuzzification in which fuzzy image‐regions are allocated to target land‐cover classes. The proposed procedure is implemented using automated statistical techniques that require very little user interaction. The results indicate that fuzzy segmentation‐based methods produce acceptable thematic accuracy and could represent a viable alternative to current crisp image segmentation approaches.     

Space–time code selection for OFDM–MISO systems

In this paper, a space–time code selection technique for multiple transmit antenna OFDM systems is proposed, and a constant-rate transmission mode for the space–time code selection technique is introduced. Subcarriers are divided into subcarrier groups and a comparison of the equivalent SISO channel envelopes with a set of predetermined threshold levels for a central subcarrier of each group is performed at the receiver, which decides on the subcarriers to be used at each antenna and sends this information to the transmitter. The transmitter adjusts the space–time code to the number of selected antennas at each subcarriers group using four bits for feedback information per group. Simulation results show that the system performs well for a range of Doppler frequencies for correlated and uncorrelated channels, outperforming transmit antenna selection techniques and adaptive transmit antenna diversity systems for both variable-rate and constant-rate transmission modes.     

A method for classification accuracy evaluation for a precipitation‐oriented classifier

A method of classification accuracy evaluation for a cloud and precipitation classifier applied to geostationary meteorological satellite data is presented. The method has been developed to evaluate the accuracy of a rather precise classification algorithm. The algorithm produces nine classes, four of which involve precipitation. The classes are: (1) clear or insignificant cloud, (2) low thin cloud with no rain, (3) low or middle thin cloud with no rain, (4) low or middle thick cloud with no rain, (5) middle or high cloud with no rain, (6) middle or high cloud with the possibility of rain, (7) middle or high cloud with light–moderate precipitation, (8) middle–high cloud with moderate–heavy precipitation, (9) heavy thunderstorm. The evaluation classifier has been tested for its accuracy (ground truth) using comparison between actual meteorological weather reports and classification results derived from the algorithm applied. For the estimation of classification accuracy, the omission/commission method is applied between the observed and the classification‐produced values. The classifier used has proved to be very reliable for classifying major cloud types and precipitation, tested during the synoptic situation of depression systems approaching the south Balkan Peninsula from the west. In that synoptic situation, different intensities of rainfall as well as heavy thunderstorm were present, and the results are very satisfactory. The method can be used to evaluate classification results produced by algorithms applied to meteorological satellite data, classifying precipitation areas as well as the heaviness of precipitation.     

Object‐oriented integration testing

Object‐oriented software development is an evolutionary process, and hence the opportunities for integration are abundant. Conceptually, classes are encapsulation of data attributes and their associated functions. Software components are amalgamation of logically and/or physically related classes. A complete software system is also an aggregation of software components. All of these various integration levels warrant contemporary integration techniques. Traditional integration techniques towards the end of software development process do not suffice any more. Integration strategies are needed at class level, component level, sub‐system level, and system levels. Classes require integration of methods. Various types of class interaction mechanisms demand different testing strategies. Integration of classes into components presses its own integration requirements. Finally, the system integration demands different types of integration testing strategies. This paper discusses the various integration levels prevalent in object‐oriented software development. The integration requirements of each level are met by suggesting a solution for the same. An integration framework for integrating classes into a system is also proposed. This revised version was published online in June 2006 with corrections to the Cover Date.     

“Virtual laboratory environment” (VLE): a software environment oriented agent and object for modeling and simulation of complex systems

Our research relates to multi-agent and oriented object modeling and simulation of the complex systems. Our research interest itself more particularly with system where the spatial and temporal component make a great part of system to model (for example, ecosystems or systems of production). Within the framework of this article, we will be interested in the flexible production systems.The simulation of complex systems requires generally the integration and the coupling of heterogeneous models (multi-agent, mathematical, and so on). This heterogeneity is a consequence of the diversity of the disciplines and abilities of designers. The approach that we develop consists in the development of “virtual laboratories ”. Our platform “virtual laboratory environment” (VLE) enables us to specify, simulate and analyze spatial complex systems. VLE is based on the concepts of reactive agents, objects and spatial and temporal multi-scale systems.     

Design on H ∞-filtering for discrete-time switched delay systems

This article is concerned with the delay-dependent H _∞-filtering problem for discrete-time switched systems with a state delay. By using the switched Lyapunov functional method and choosing a new Lyapunov–Krasovskii functional, and, furthermore, utilising the linearisation technique, sufficient conditions on the existence of a desired filter are formulated as strict linear matrix inequalities. Neither model transformation nor the bounding technique for cross-terms is involved. A numerical example is provided to illustrate the effectiveness of the proposed method.     

Object‐oriented classification for urban land cover mapping with ASTER imagery

This document demonstrates the potential of using an object‐oriented approach to map urban land cover. One objective of this work was to test the ability of the object‐oriented classification in the generation of urban land cover maps. Anotehr was to produce an updated land cover map for the city of Beijing from Advanced Spaceborne Thermal Emission and Reflecton Radiometer (ASTER) data, with an evaluation of its accuracy.     

Modified Nyquist analysis for PFM‐continuous-time hybrid systems

A graphical method is proposed for analysing PFM‐continuous-time hybrid systems. The method is an improved version of the authors' earlier method, which was practical, but had two shortcomings that remained to be addressed. One is that the influence of the included parameter upon stability estimation is not clear, the other being that extension to the network case is not straightforward. The present paper proposes a modified Nyquist analysis method that can overcome the above two problems with little effect on sharpness in the estimation of stability.     

Design of cascade controllers for zero assignment in multivariable systems†

The paper describes a method for the design of a constant cascade controller to assign some zeros and numerator coefficients of the (open or closed-loop) transfer function matrix of a linear multivariable system. The cascade controller does not affect the poles of the system which can be positioned prior to the zero assignment. The requirements on the transfer function matrix for arbitrary assignment of some zeros and numerator coefficients are discussed. The cascade controller is calculated from sets of simple linear equations and thus the method is computationally very efficient. An interactive computer programme is described for the computer-aided design of cascade controllers. Finally, two simple numerical examples of zero assignment in open-loop and closed-loop systems are worked out in detail to illustrate the method.     

Object‐oriented classification of sidescan sonar data for mapping benthic marine habitats

This research presents an object‐oriented technique for habitat classification at different segmentation levels based on the use of imagery from an Edgetech 272 side scan sonar. We investigate the success of object parameters such as shape and size as well as texture in discriminating reef from sand habitat. The results are evaluated using traditional digitization, based on visual assessment of the sidescan imagery, and video transects. Whereas the application of traditional pixel‐based classification results in a pixelized (salt and pepper) representation of habitat distribution, the object‐based classification technique results in habitat objects (raster or vector). The object‐oriented classification results are cross‐validated using confusion matrices in image classification software and error matrices from underwater video transects showing an overall accuracy of 80% based on two classes within the image at three segmentation levels and an overall accuracy of 60% based on three classes at two segmentation levels. This is compared with the digitized layer accuracy of 81% for two classes and 72% for three classes, and this demonstrates the successful application of object‐oriented methods for habitat mapping. This technique retains spatially discrete habitat pattern information in a classified vector shape file with methods that are automated, repeatable, objective, and capable of processing many sidescan records in a more efficient manner.     

Land use studies in drylands: an evaluation of object‐oriented classification of very high resolution panchromatic imagery

Object‐oriented classification approaches offer an alternative to per‐pixel methods for assessment of land use and land cover. Combining object‐oriented approaches with very high resolution imagery may provide enhanced possibilities for applications requiring land use and land cover data. The aim of this study is to evaluate the application of object‐oriented classification of panchromatic very high resolution data in African drylands, where sizes and shapes of fields are varied, and intercropping practised, which might lead to difficulties in image segmentation. The results show that region‐based segmentation is sensitive to the proportion of spectral and shape information and the best results were gained when the segmentation was based on predominately spectral information. The accuracy (Kappa value of 0.6) for the object‐oriented classification was significantly higher than that for per‐pixel classification. However, both the segmentation and the classification were time‐consuming based on a trial and error process.     

Design methodology for battery powered embedded systems — In safety critical application

Battery powered embedded system can be considered as a power aware system for a safety critical application. There is a need of saving the battery power for such power aware system so that it can be used more efficiently, particularly in safety critical applications. Present paper describes power optimization procedure using real time scheduling technique having a specific dead line guided by the model based optimum current discharge profile of a battery. In any power aware system ‘energy optimization’ is one of the major issues for a faithful operation.     

Design of output feedback proportional–integral controller for polynomial fuzzy systems

In this paper, the design of dynamic output feedback control law for polynomial fuzzy systems is studied. The main purpose is to design a tracker control law for fuzzy polynomial systems that are subject to external bounded disturbances. The structure of the control law is considered as fuzzy proportional–integral control. The conditions for deriving the control law are formulated in the form of a sum of square (SOS) feasibility problem. The designed control law will be able to force the system state vector to follow the state vector of a stable reference model in addition to guaranteeing the performance measure. The simulation results show the efficiency of the proposed method exposed to external disturbance.     

Scalable mpNoC for massively parallel systems – Design and implementation on FPGA

The high chip-level integration enables the implementation of large-scale parallel processing architectures with 64 and more processing nodes on a single chip or on an FPGA device. These parallel systems require a cost-effective yet high-performance interconnection scheme to provide the needed communications between processors. The massively parallel Network on Chip (mpNoC) was proposed to address the demand for parallel irregular communications for massively parallel processing System on Chip (mppSoC). Targeting FPGA-based design, an efficient mpNoC low level RTL implementation is proposed taking into account design constraints. The proposed network is designed as an FPGA based Intellectual Property (IP) able to be configured in different communication modes. It can communicate between processors and also perform parallel I/O data transfer which is clearly a key issue in an SIMD system. The mpNoC RTL implementation presents good performances in terms of area, throughput and power consumption which are important metrics targeting an on chip implementation. mpNoC is a flexible architecture that is suitable for use in FPGA-based parallel systems. This paper introduces the basic mppSoC architecture. It mainly focuses on the mpNoC flexible IP based design and its implementation on FPGA. The integration of mpNoC in mppSoC is also described. Implementation results on a Stratix II FPGA device are given for three data-parallel applications ran on mppSoC. The obtained good performances justify the effectiveness of the proposed parallel network. It is shown that the mpNoC is a lightweight parallel network making it suitable for both small as well as large FPGA-based parallel systems.     

Comments on ‘Design of decentralized reliable controllers for large-scale systems’

It is pointed out that the design algorithm given by Darwish and Soliman (1988) in the title paper is improper.