In areas as diverse as earth remotesensing, astronomy, and medical imaging, image acquisition technology has undergone tremendous improvements in recent years. The vast amounts of scientific data are potential treasu...
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In areas as diverse as earth remotesensing, astronomy, and medical imaging, image acquisition technology has undergone tremendous improvements in recent years. The vast amounts of scientific data are potential treasure-troves for scientific investigation and analysis. Unfortunately, advances in our ability to deal with this volume of data in an effective manner have not paralleled the hardware gains. While special-purpose tools for particular applications exist, there is a dearth of useful general-purpose software tools and algorithms which can assist a scientist in exploring large scientific image databases. This paper presents our recent progress in developing interactive semi-automated image database exploration tools based on patternrecognition and machine learning technology. We first present a completed and successful application that illustrates the basic approach: the SKICAT system used for the reduction and analysis of a 3 terabyte astronomical data set. SKICAT integrates techniques from imageprocessing, data classification, and database management. It represents a system in which machine learning played a powerful and enabling role, and solved a difficult, scientifically significant problem. We then proceed to discuss the general problem of automated image database exploration, the particular aspects of image databases which distinguish them from other databases, and how this impacts the application of off-the-shelf learning algorithms to problems of this nature. A second large image database is used to ground this discussion: Magellan's images of the surface of the planet Venus. The paper concludes with a discussion of current and future challenges.
A prototype binary edge-extracting ('smart') custom image sensor array, 'Edge 1', was developed previously at the University of Brighton, Awcock. It was implemented in a 2 micron ES2 CMOS process and f...
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A prototype binary edge-extracting ('smart') custom image sensor array, 'Edge 1', was developed previously at the University of Brighton, Awcock. It was implemented in a 2 micron ES2 CMOS process and featured 72 I/O pins because of its total lack of on-chip support circuitry. Several detail changes were suggested by testing this prototype and many of these have been recently tested in a 1.5 micron ES2 CMOS re-implementation of this design, 'Edge 2'. The successful operation of the Edge 1 prototype has shown that general-purpose CMOS manufacturing processes such as that offered by ES2 are indeed a practical proposition for the integration of imagesensing and processing functions. The uniformity of the photo-sites produced has been very encouraging.
This article deals with the processing of already classified satellite images according to land use in order to remove ambiguities, i.e. mistakes in labels. Those images have already been classified with the maximum l...
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This article deals with the processing of already classified satellite images according to land use in order to remove ambiguities, i.e. mistakes in labels. Those images have already been classified with the maximum likehood method but some classes are not correctly determined. For the elimination of ambiguities in this kind of class, we applied our method of determination of land use mixture in pixels. We first briefly review our method of determination of land use mixture. Then we explain how we deal with ambiguities in labels of the maximum likehood classification. We finish with three examples of satellite images that have not correctly been classified. The first one is the vineyard case. Another example for naked soil and urban zone. The last one is a forestry survey application, the determination of the planted pines density.
Fingerprint verification systems are expensive and complex, requiring sensing facilities, pre-processing algorithms for image quality enhancement and procedures for ridge and minutiae detection which can be used for c...
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ISBN:
(纸本)0780326288
Fingerprint verification systems are expensive and complex, requiring sensing facilities, pre-processing algorithms for image quality enhancement and procedures for ridge and minutiae detection which can be used for classification, verification and recognition. To-date, the main published approaches to fingerprint recognition break down the process of ridge detection into smoothing or early pre-processing, edge detection, thresholding, binarization and subsequently thinning. This whole procedure can be very computationally expensive and hence require more expensive hardware to meet the response-time requirements. The approach presented in this paper is based on fuzzy logic techniques. This has the advantage of being simple and less expensive.
We have developed a device called Active Eye sensing System which is consisted of stereo camera. Each camera has 2 DOF that gives a wide view of 3D space. Using AESS, we extract a moving object from the scene, keep tr...
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ISBN:
(纸本)0780330269
We have developed a device called Active Eye sensing System which is consisted of stereo camera. Each camera has 2 DOF that gives a wide view of 3D space. Using AESS, we extract a moving object from the scene, keep tracking, and give its position and velocity. High speed correlation Method is used to achieve realtime imageprocessing. As one of applications, we have exhibited NetWork Neuro Baby in SIGGRAPH'95 held in Los Angeles.
Groundwater management nowadays is mainly governed by hydrogeological aspects of groundwater occurrences. However, focussing on groundwater as a natural resource of the landscape, there is a deficit in spatial informa...
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ISBN:
(纸本)0819416444
Groundwater management nowadays is mainly governed by hydrogeological aspects of groundwater occurrences. However, focussing on groundwater as a natural resource of the landscape, there is a deficit in spatial information about the ecological factors influencing the water balance. It becomes more important to assess the ecological role of groundwater in accordance to its quality and quantity as well as to predict risks by changes in the landscape such as lowering groundwater level and nitrate leaching. Due to high spatial diversity in the pattern of land use, relief attributes and soil properties, ecological data have to distinguish different homogeneous site units. remotesensing data with high resoluted geometry would have the potential to improve the spatial information about landscape and its water balance. In many regions an aggravating deficit between the groundwater consumption and the recharge of groundwater can be observed. This situation is characterized by two effects: (1) Increasing groundwater consumption. (2) Decreasing recharge of groundwater. A higher level of surface sealing can be found in agriculture as well as in urban areas. Evapotranspiration in plant production has increased. By intensification in agriculture plant production has generated more biomass and crop yield. But for every unit of yield and biomass, the plant has to transpirate additional soil water. Therefore, higher intensity in farming is related to higher water consumption by the process of evapotranspiration.
The proceeding contains 226 papers. Topics discussed include underwater and acoustic applications in signal processing, environmental sensing, design and implementation of signal processing systems, signal processing ...
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The proceeding contains 226 papers. Topics discussed include underwater and acoustic applications in signal processing, environmental sensing, design and implementation of signal processing systems, signal processing in astronomy and space physics, biomedical imaging, neurological signal processing, automotive signal processing, echo cancellation, audio and electroacoustics, wideband coding, time delay estimation and equalization, hardware for image and video coding, neural network application to speech processing, patternrecognition, language identification, arrays and underwater acoustics, system identification and classification, sonar beamforming, and radars.
This paper deals with the problem of unsupervised classification of images modeled by Markov Random Fields (MRF). If the model parameters are known then we have various methods to solve the segmentation problem (simul...
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ISBN:
(纸本)0818670428
This paper deals with the problem of unsupervised classification of images modeled by Markov Random Fields (MRF). If the model parameters are known then we have various methods to solve the segmentation problem (simulated annealing, ICM, etc...). However, when they are not known, the problem becomes more difficult. One has to estimate the hidden label field parameters from the only observable image. Our approach consists of extending a recent iterative method of estimation, called Iterative Conditional Estimation (ICE) to a hierarchical markovian model. The idea resembles the Estimation-Maximization (EM) algorithm as we recursively look at the Maximum a Posteriori (MAP) estimate of the label field given the estimated parameters then we look at the Maximum Likelihood (ML) estimate of the parameters given a tentative labeling obtained at the previous step. We propose unsupervised image classification algorithms using a hierarchical model. The only parameter supposed to be known is the number of regions, all the other parameters are estimated. The presented algorithms have been implemented on a Connection Machine CM200. Comparative tests have been done on noisy synthetic and real images (remotesensing).
Nonlinear modeling and solution techniques of array algebra are applied to the problem of simultaneous graph matching and photogrammetric bundle adjustment. Graph matching provides automatically the image coordinates ...
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ISBN:
(纸本)0819418390
Nonlinear modeling and solution techniques of array algebra are applied to the problem of simultaneous graph matching and photogrammetric bundle adjustment. Graph matching provides automatically the image coordinates and 2 × 2 weight matrices of `control entities', points and vertices of known relative geometrical shape which replace the control points used in traditional bundle adjustment. Inclusion of multiple control entities to cover the entire image area of interest allows the use of a fast new array algebra formation of real-time bundle adjustment to act as the pull-in mechanism for the global graph matching process. The resulting integrated solution of Feature Entity Least Squares Matching (FELSM) is very fast and produces high quality results. FELSM has demonstrated solutions to several problems of ongoing research interest in photogrammetry and the related fields of image understanding, patternrecognition and computer vision. These results open the way for further integration of the various fields.
Desertification of the Damagaram region (Sahelian zone of Niger) is represented by several processes: decrease or modification of the vegetation, deflation of sandy soils by the wind and exhumation of lateritic crusts...
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ISBN:
(纸本)0819416444
Desertification of the Damagaram region (Sahelian zone of Niger) is represented by several processes: decrease or modification of the vegetation, deflation of sandy soils by the wind and exhumation of lateritic crusts, modification of the pattern of dunes, increase of erosion by water. A field survey was performed by a pluridisciplinary team in order to observe and define the expressions of desertification. The spectral signatures of various soils, rocks and vegetation were measured using a high resolution field spectroradiometer. The measured spectral properties of well defined objects were used to validate the calibration of the satellite data and to define the endmembers in models of spectral unmixing. Landsat multi spectral scanner (MSS) scenes of March 11, 1973 and January 10, 1976, and a thematic mapper (TM) scene of January 4, 1987, were made compatible, and several techniques of imageprocessing were tested and compared: ratios (leaf area index, normalized difference vegetation index, redness, clay index), principal components analysis and spectral unmixing. The interpretation of the resulting images allowed a semi-quantitative monitoring of the evolution of the significant components of the landscape. Local variations of soils and vegetation are particularly well enhanced, whereas the global situation did not change drastically from 1973 to 1987.
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