Topological correction of hypertextured implicit surfaces for ray casting

Hypertextures are a useful modelling tool in that they can add three-dimensional detail to the surface of otherwise smooth objects. Hypertextures can be rendered as implicit surfaces, resulting in objects with a complex but well defined boundary. However, representing a hypertexture as an implicit surface often results in many small parts being detached from the main surface, turning an object into a disconnected set. Depending on the context, this can detract from the realism in a scene where one usually does not expect a solid object to have clouds of smaller objects floating around it. We present a topology correction technique, integrated in a ray casting algorithm for hypertextured implicit surfaces, that detects and removes all the surface components that have become disconnected from the main surface. Our method works with implicit surfaces that are C2 continuous and uses Morse theory to find the critical points of the surface. The method follows the separatrix lines joining the critical points to isolate disconnected components

Image understanding and feature extraction for applications in industry and mapping

Bibliography: p. 212-220.The aim of digital photogrammetry is the automated extraction and classification of the three dimensional information of a scene from a number of images. Existing photogrammetric systems are semi-automatic requiring manual editing and control, and have very limited domains of application so that image understanding capabilities are left to the user. Among the most important steps in a fully integrated system are the extraction of features suitable for matching, the establishment of the correspondence between matching points and object classification. The following study attempts to explore the applicability of pattern recognition concepts in conjunction with existing area-based methods, feature-based techniques and other approaches used in computer vision in order to increase the level of automation and as a general alternative and addition to existing methods. As an illustration of the pattern recognition approach examples of industrial applications are given. The underlying method is then extended to the identification of objects in aerial images of urban scenes and to the location of targets in close-range photogrammetric applications. Various moment-based techniques are considered as pattern classifiers including geometric invariant moments, Legendre moments, Zernike moments and pseudo-Zernike moments. Two-dimensional Fourier transforms are also considered as pattern classifiers. The suitability of these techniques is assessed. These are then applied as object locators and as feature extractors or interest operators. Additionally the use of fractal dimension to segment natural scenes for regional classification in order to limit the search space for particular objects is considered. The pattern recognition techniques require considerable preprocessing of images. The various image processing techniques required are explained where needed. Extracted feature points are matched using relaxation based techniques in conjunction with area-based methods to 'obtain subpixel accuracy. A subpixel pattern recognition based method is also proposed and an investigation into improved area-based subpixel matching methods is undertaken. An algorithm for determining relative orientation parameters incorporating the epipolar line constraint is investigated and compared with a standard relative orientation algorithm. In conclusion a basic system that can be automated based on some novel techniques in conjunction with existing methods is described and implemented in a mapping application. This system could be largely automated with suitably powerful computers

Computer-generated global map of valley networks on Mars

The presence of valley networks (VN) on Mars suggests that early Mars was warmer and wetter than present. However, detailed geomorphic analyses of individual networks have not led to a consensus regarding their origin. An additional line of evidence can be provided by the global pattern of dissection on Mars, but the currently available global map of VN, compiled from Viking images, is incomplete and outdated. We created an updated map of VN by using a computer algorithm that parses topographic data and recognizes valleys by their morphologic signature. This computer-generated map was visually inspected and edited to produce the final updated map of VN. The new map shows an increase in total VN length by a factor of 2.3. A global map of dissection density, D, derived from the new VN map, shows that the most highly dissected region forms a belt located between the equator and mid-southern latitudes. The most prominent regions of high values of D are the northern Terra Cimmeria and the Margaritifer Terra where D reaches the value of 0.12 km−1 over extended areas. The average value of D is 0.062 km−1, only 2.6 times lower than the terrestrial value of D as measured in the same fashion. These relatively high values of dissection density over extensive regions of the planet point toward precipitation-fed runoff erosion as the primary mechanism of valley formation. Assuming a warm and wet early Mars, peculiarity of the global pattern of dissection is interpreted in the terms of climate controlling factors influenced by the topographic dichotomy

Information Extraction and Modeling from Remote Sensing Images: Application to the Enhancement of Digital Elevation Models

To deal with high complexity data such as remote sensing images presenting metric resolution over large areas, an innovative, fast and robust image processing system is presented. The modeling of increasing level of information is used to extract, represent and link image features to semantic content. The potential of the proposed techniques is demonstrated with an application to enhance and regularize digital elevation models based on information collected from RS images

Content-based image retrieval of museum images

Content-based image retrieval (CBIR) is becoming more and more important with the advance of multimedia and imaging technology. Among many retrieval features associated with CBIR, texture retrieval is one of the most difficult. This is mainly because no satisfactory quantitative definition of texture exists at this time, and also because of the complex nature of the texture itself. Another difficult problem in CBIR is query by low-quality images, which means attempts to retrieve images using a poor quality image as a query. Not many content-based retrieval systems have addressed the problem of query by low-quality images. Wavelet analysis is a relatively new and promising tool for signal and image analysis. Its time-scale representation provides both spatial and frequency information, thus giving extra information compared to other image representation schemes. This research aims to address some of the problems of query by texture and query by low quality images by exploiting all the advantages that wavelet analysis has to offer, particularly in the context of museum image collections. A novel query by low-quality images algorithm is presented as a solution to the problem of poor retrieval performance using conventional methods. In the query by texture problem, this thesis provides a comprehensive evaluation on wavelet-based texture method as well as comparison with other techniques. A novel automatic texture segmentation algorithm and an improved block oriented decomposition is proposed for use in query by texture. Finally all the proposed techniques are integrated in a content-based image retrieval application for museum image collections

Discrimination of Textures Using Texton Patterns

Textural patterns can often be used to recognize familiar objects in an image or retrieve images with similar texture from a database. Texture patterns can provide significant and abundance of texture and shape information. One of the recent significant and important texture features called Texton represents the various patterns of image which is useful in texture analysis. The present paper is an extension of our previous paper [1]. The present paper divides the 3 D7; 3 neighbourhood into two different 2 D7; 2 neighbourhood grids each consist four pixels. On this 2 D7; 2 grids shape descriptor indexes (SDI) are evaluated separately and added to form a Total Shape Descriptor Index Image (TSDI). By deriving textons on TSDI image Total Texton Shape Matrix (TTSM) image is formed and Grey Level Co-Occurence Matrix (GLCM) parameters are derived on it for efficient texture discrimination. The experimental result shows the efficacy of the present metho

Multi-texture image segmentation

Visual perception of images is closely related to the recognition of the different texture areas within an image. Identifying the boundaries of these regions is an important step in image analysis and image understanding. This thesis presents supervised and unsupervised methods which allow an efficient segmentation of the texture regions within multi-texture images. The features used by the methods are based on a measure of the fractal dimension of surfaces in several directions, which allows the transformation of the image into a set of feature images, however no direct measurement of the fractal dimension is made. Using this set of features, supervised and unsupervised, statistical processing schemes are presented which produce low classification error rates. Natural texture images are examined with particular application to the analysis of sonar images of the seabed. A number of processes based on fractal models for texture synthesis are also presented. These are used to produce realistic images of natural textures, again with particular reference to sonar images of the seabed, and which show the importance of phase and directionality in our perception of texture. A further extension is shown to give possible uses for image coding and object identification

Mètode d'extracció multiparamètrica de característiques de textura orientat a la segmentació d'imatges

Tal com es veurà en el següent capítol d'antecedents, existeixen formes molt variades d'afrontar l'anàlisi de textures però cap d'elles està orientada al càlcul en temps real (video rate). Degut a la manca de mètodes que posin tant d'èmfasi en el temps de processat, l'objectiu d'aquesta tesi és definir i desenvolupar un nou mètode d'extracció de característiques de textura que treballi en temps real. Per aconseguir aquesta alta velocitat d'operació, un altre objectiu és presentar el disseny d'una arquitectura específica per implementar l'algorisme de càlcul dels paràmetres de textura definits, així com també l'algorisme de classificació dels paràmetres i la segmentació de la imatge en regions de textura semblant.En el capítol 2 s'expliquen els diversos mètodes més rellevants dins la caracterització de textures. Es veuran els mètodes més importants tant pel que fa als enfocaments estadístics com als estructurals. També en el mateix capítol se situa el nou mètode presentat en aquesta tesi dins els diferents enfocaments principals que existeixen. De la mateixa manera es fa una breu ressenya a la síntesi de textures, una manera d'avaluar quantitativament la caracterització de la textura d'una imatge. Ens centrarem principalment, en el capítol 3, en l'explicació del mètode presentat en aquest treball: s'introduiran els paràmetres de textura proposats, la seva necessitat i definicions. Al ser paràmetres altament perceptius i no seguir cap model matemàtic, en aquest mateix capítol s'utilitza una tècnica estadística anomenada anàlisi discriminant per demostrar que tots els paràmetres introdueixen suficient informació per a la separabilitat de regions de textura i veure que tots ells són necessaris en la discriminació de les textures.Dins el capítol 4 veurem com es tracta la informació subministrada pel sistema d'extracció de característiques per tal de classificar les dades i segmentar la imatge en funció de les seves textures. L'etapa de reconeixement de patrons es durà a terme en dues fases: aprenentatge i treball. També es presenta un estudi comparatiu entre diversos mètodes de classificació de textures i el mètode presentat en aquesta tesi; en ell es veu la bona funcionalitat del mètode en un temps de càlcul realment reduït. S'acaba el capítol amb una anàlisi de la robustesa del mètode introduint imatges amb diferents nivells de soroll aleatori. En el capítol 5 es presentaran els resultats obtinguts mitjançant l'extracció de característiques de textura a partir de diverses aplicacions reals. S'aplica el nostre mètode en aplicacions d'imatges aèries i en entorns agrícoles i sobre situacions que requereixen el processament en temps real com són la segmentació d'imatges de carreteres i una aplicació industrial d'inspecció i control de qualitat en l'estampació de teixits. Al final del capítol fem unes consideracions sobre dos efectes que poden influenciar en l'obtenció correcta dels resultats: zoom i canvis de perspectiva en les imatges de textura.En el capítol 6 es mostrarà l'arquitectura que s'ha dissenyat expressament per al càlcul dels paràmetres de textura en temps real. Dins el capítol es presentarà l'algorisme per a l'assignació de grups de textura i es demostrarà la seva velocitat d'operació a video rate.Finalment, en el capítol 7 es presentaran les conclusions i les línies de treball futures que es deriven d'aquesta tesi, així com els articles que hem publicat en relació a aquest treball i a l'anàlisi de textures. Les referències bibliogràfiques i els apèndixs conclouen el treball

The efficient use of data from different sources for production and application of digital elevation models

The emphasis of the investigation reported in this thesis is on the use of digital elevation data of two resolutions originating from two different sources. The high resolution DEM was captured from aerial photographs (first source) at a scale of 1:30,000 and the low resolution DEM was captured from SPOT images (second source). It is well known that the resolution of DEM data depends a great deal on the scale of the images used. The technique for capturing DEMs is static measurement of the spot heights in a regular grid. The grid spacing of the high resolution DEM was 30 m, and of the low resolution DEM was 100 m. The aims of this thesis are as follows: 1. To assess the feasibility of using SPOT stereodata as a source of height information and merged with data from aerial photography. This is carried out by comparison of the elevation data derived from SPOT with the digital elevation data derived from aerial photography. From the comparison of these two sources of height information, some results are derived which show the possible heighting accuracy levels which can realistically be achieved. A systematic error in the estimated average of the elevation differences was found and many tests have been carried out to find the reasons for the presence of this systematic error. 2. To develop methods to manipulate the captured data. 2.1. Gross error (blunder) detection. Blunders made during the data capturing procedure affect the accuracy of the final product. Therefore it is necessary to trap and to remove them. A pointwise local self-checking blunder detection algorithm was developed in order to check the grid elevation data, particularly those which are derived from the second source. 2.2. Data coordinates transformation. The data must be transformed into a common projection in order to be directly comparable. The projection and coordinate systems employed are studied in this project, and the errors caused by the transformations are estimated. 2.3. Data merging. Data of different reliability have to be merged into a single set of data. In this project data from two different sources are merged in order to create a final product of known and uniform accuracy. The effect of the lower resolution source on the high resolution source was studied, in dense and in sparse form. 2.4. Data structure. To structure the data by changing the format in order to be in an acceptable form for DEM creation and display, through the commercially available Laser-Scan package DTMCREATE. 3. DEM production and contouring. To produce DEMs from the initial data and that derived from the two merged sources, and to find the accuracy of the interpolation procedure by comparing the derived interpolated data with the high resolution DEM which has been derived from aerial photography. Finally to interpolate contours directly from the "raw" SPOT data and to compare them with those derived from the aerial photography in order to find out the feasibility and capability of using SPOT data in contouring for topographic maps

SPATIAL VARIABILITY IN FOREST FUELS: SIMULATION MODELING AND EFFECTS ON FIRE BEHAVIOR

Forests in the western United States and elsewhere face a growing crisis arising from global warming, changes in fuel beds and an increasing human population. Fire management policy emphasizes fuel treatments, such as thinning and prescribed burning, to remedy this situation because fuels are the one component of the problem that we can directly affect through management action. At present, however, the tools we have for the evaluation of fuel treatments are inadequate because they do not describe the fuel bed, or effects of modifications to the fuel bed on fire behavior in sufficient detail. The work described here presents a system that has potential to address the shortcomings of current approaches. In the first chapter, to improve our ability to represent wildland fuels, a three dimensional spatially explicit fuel model, FUEL3D, is presented which represents fuels at a level of detail comparable to what we can actually measure: stands as collections of individual trees, with branches and foliage. In conjunction with new, physical fire models, detailed fire behavior simulations can be carried out using fuels represented with FUEL3D as inputs. This system thus comprises a simulation laboratory which will greatly enhance our capabilities to evaluate fuel treatments and strengthen our understanding of fire and fuel interactions. In the second chapter, this system is demonstrated in an exploratory simulation study which examines the impact of spatial variability within an individual tree crown on fire behavior. Results demonstrate that the distribution of fuel within a tree crown significantly affects the rate of fuel consumption, as well as the timing, duration and magnitude of heat produced. This suggests that modeling of both crown fire initiation and propagation would benefit from more detailed description of crown fuels. In third chapter a replicated series of stand scale fire simulations is carried out to examine variability in forward spread rate; accelerated spread rates endanger fire fighters. Substantial variability is observed to arise from fine scale fuel-atmosphere-fire interactions which are not easily predicted beforehand. A new strategy is proposed in which physical fire models are used to quantify the potential drivers of variability in fire behavior