Recent developments in commercial satellite products have resulted in a broader range of high quality image data, enabling detailed analysis. Transportation features have historically been difficult to accurately identify and structure into coherent networks; prior analyses have demonstrated problems in locating smaller features. One problem is that roadways in urban environments are often partly obscured by proximity to land cover or impervious objects. Ongoing research has focused on object-based methods for classification and different segmentation techniques key to this approach. For this application, software packages such as eCognition have shown encouraging results in assessing spatial and spectral patterns at varied scales in intelligent classification of aerial and satellite imagery. In this study 2.44m QuickBird and 4m Ikonos multispectral imagery for a 7.5' quad near the Mississippi Gulf Coast are examined. Challenges in analysis include intricate networks of smaller roads in residential zones and regions of tall/dense tree cover. Both spectral and object-based approaches are implemented for pre-classification, and road features are extracted using various techniques, after which the results are compared based on a ?Raster Completeness? model developed.

This thesis addresses three research gaps in published literature. These are, the absence of Object Based Image Analysis (OBIA) methods for urban Land Use and Land Cover (LULC) analysis in Nigeria; the inability to use Nigeriasat-1 satellite data for urban LULC analysis and monitoring urban growth in Nigeria with Shannon’s Entropy Index. Using Abuja as a case study, this research investigated the nature of land use/land cover change (LULCC). Specific objectives were: design of an object based classification method to extract urban LULC; validate a method to extract LULC in developing countries from multiple sources of remotely sensed data; apply the method to extract LULC data; use the outputs to validate an Urban Growth Model (UGM); optimise an UGM to represent patterns and trends and through this iterative process identify and prioritise the driving forces of urban change; and finally use the outputs of the land use maps to determine if planning has controlled land use development. Landsat 7 ETM (2001), Nigeriasat-1 SLIM (2003) and SPOT 5 HRG (2006) sensor data were merged with land use cadastre in OBIA, to produce land use maps. Overall classification accuracies were 92%, 89% and 96% respectively. Post classification analysis of LULCC indicated 4.43% annual urban spread. Shannon’s Entropy index for the study period were 0.804 (2001), 0.898 (2003) and 0.930 (2006). Cellular Automata/Markov analysis was also used to predict urban growth trend of 0.89% per annum. For the first time OBIA has been used for LULC analysis in Nigeria. This research has established that Nigeriasat-1 data can contribute to urban studies using innovative OBIA methods. In addition, that Shannon’s Entropy Index can be used to understand the nature of urban growth in Nigeria. Finally, the drivers of LULCC in Abuja are similar to those of planned capital cities in other developing economies. Land use developments in Abuja can provide an insight into urban dynamics in a developing country’s capital region. OBIA, Shannon’s Entropy Index and UGM can aid urban administrators and provide information for sustainable urban planning and development.

[pt] Esta tese examina e apresenta contribuições para a codificação de textura intra-quadro na codificação de imagens baseada em objeto. Duas abordagens de codificação são focadas: a DCT baseada em blocos e a DCT adaptativa à forma (SA-DCT). São propostos indicadores morfológicos para extrair características de forma e textura intrínsecas ao objeto a ser codificado, classificando os blocos de imagem 8 X 8 segundo o número de pixels do objeto neles contidos. Esses indicadores são utilizados para a análise de algoritmos de codificação conhecidos na literatura e também para a proposição de esquemas híbridos que solucionem problemas identificados. Os esquemas híbridos propostos baseiam-se no tratamento diferenciado para grupos de blocos distintos, usando como base a informação sobre a textura média nesses grupos. Por fim, é proposta uma estrutura de codificação adaptativa em função da taxa de bits, da textura e da forma do objeto a ser codificado. Essa estratégia incorpora os esquemas híbridos propostos nesta tese para a escolha da direção preferencial de processamento do algoritmo de extrapolação EI - Extension Interpolation - e da SA-DCT. Ela seleciona automaticamente a abordagem de codificação mais adequada a um grupo específico de blocos a cada faixa de taxas de bits, valendo- se dos indicadores morfológicos. O codificador adaptativo proposto mostrou-se equivalente ou superior em desempenho aos melhores esquemas conhecidos na literatura, tanto para taxas baixas, quanto para taxas altas. Os resultados podem ser verificados a partir das curvas de desempenho e também a partir da observação da qualidade subjetiva das imagens recuperadas. / [en] This thesis examines and presents contributions to the intra-frame texture coding of Object-Based Image Coding. Two coding approaches are focused: the block-based DCT and the shape-adaptive DCT (SA-DCT). Morphological features are proposed in order to extract intrinsic characteristics of shape and texture from the object to be encoded. These features classify the 8 X 8 image blocks according to their number of object pixels. These morphological features are used both in the analysis of coding algorithms reported in the literature and in the design of hybrid schemes that overcome some problems identified during the analysis procedure. The proposed hybrid schemes employ different strategies to deal with different groups of blocks. The information about the mean texture value at these groups is used as the basis of the algorithms. Finally, an adaptive coding structure, which is a function of the bit rate, texture and shape of the object, is proposed. This strategy incorporates the hybrid schemes introduced in this thesis, in order to choose the preferential processing direction for the EI - Extension Interpolation - padding technique and for the SA-DCT. It automatically selects the more adequate approach for a specific group of blocks at a given bit rate, depending on the morphological features. Performance of this adaptive coding scheme is either comparable or better than the best object-based transform coding schemes reported in the literature. This is valid both at low and high bit rates. Results are presented in terms of PSNR performance curves and subjective quality of the decoded images.

For landscapes dominated by agriculture, land cover plays an important role in the balance between anthropogenic and natural forces. Therefore, the objective of this thesis is to describe two different methodologies that have been implemented to create high-resolution land cover classifications in a dominant agricultural landscape. First, an object-based segmentation approach will be presented, which was applied to historic, high resolution, panchromatic aerial photography. Second, a traditional per-pixel technique was applied to multi-temporal, multispectral, high resolution aerial photography, in combination with light detection and ranging (LIDAR) and independent component analysis (ICA). A critical analysis of each approach will be discussed in detail, as well as the ability of each methodology to generate landscape metrics that can accurately characterize the quality of the landscape. This will be done through the comparison of various landscape metrics derived from the different classifications approaches, with a goal of enhancing the literature concerning how these metrics vary across methodologies and across scales. This is a familiar problem encountered when analyzing land cover datasets over time, which are often at different scales or generated using different methodologies. The diversity of remotely sensed imagery, including varying spatial resolutions, landscapes, and extents, as well as the wide range of spatial metrics that can be created, has generated concern about the integrity of these metrics when used to make inferences about landscape quality. Finally, inferences will be made about land cover and land cover change dynamics for the state of Iowa based on insight gained throughout the process.

Forest ecosystems have recently received worldwide attention due to their biological diversity and their major role in the global carbon balance. Detecting forest cover change is crucial for reporting forest status and assessing the evolution of forested areas. However, existing change detection approaches based on satellite remote sensing are not quite appropriate to rapidly process the large volume of earth observation data. Recent advances in image segmentation have led to new opportunities for a new object-based monitoring system. <br> <br> This thesis aims at developing and evaluating an automated object-based change detection method dedicated to high spatial resolution satellite images for identifying and mapping forest cover changes in different ecosystems. This research characterized the spectral reflectance dynamics of temperate forest stand cycle and found the use of several spectral bands better for the detection of forest cover changes than with any single band or vegetation index over different time periods. Combining multi-date image segmentation, image differencing and a dedicated statistical procedure of multivariate iterative trimming, an automated change detection algorithm was developed. This process has been further generalized in order to automatically derive an up-to-date forest mask and detect various deforestation patterns in tropical environment.<br> <br> Forest cover changes were detected with very high performances (>90 %) using 3 SPOT-HRVIR images over temperate forests. Furthermore, the overall results were better than for a pixel-based method. Overall accuracies ranging from 79 to 87% were achieved using SPOT-HRVIR and Landsat ETM imagery for identifying deforestation for two different case studies in the Virunga National Park (DRCongo). Last but not least, a new multi-scale mapping solution has been designed to represent change processes using spatially-explicit maps, i.e. deforestation rate maps. By successfully applying these complementary conceptual developments, a significant step has been done toward an operational system for monitoring forest in various ecosystems.

Linear mixed models (LMMs) provide a still underused methodological perspective on combining experimental and individual-differences research. Here we illustrate this approach with two-rectangle cueing in visual attention (Egly et al., 1994). We replicated previous experimental cue-validity effects relating to a spatial shift of attention within an object (spatial effect), to attention switch between objects (object effect), and to the attraction of attention toward the display centroid (attraction effect), also taking into account the design-inherent imbalance of valid and other trials. We simultaneously estimated variance/covariance components of subject-related random effects for these spatial, object, and attraction effects in addition to their mean reaction times (RTs). The spatial effect showed a strong positive correlation with mean RT and a strong negative correlation with the attraction effect. The analysis of individual differences suggests that slow subjects engage attention more strongly at the cued location than fast subjects. We compare this joint LMM analysis of experimental effects and associated subject-related variances and correlations with two frequently used alternative statistical procedures

Neurologically normal individuals show a leftward spatial bias and tend to collide with objects on the right side more frequently than on the left. The upper visual field is associated with extrapersonal space, and mediated by the ventral stream through parvocellular projections. The lower visual field is associated with peripersonal space, and mediated by the dorsal stream through magnocellular projections. Upper and lower visual field differences have been observed in perceptual asymmetries but results have been mixed. Object- and space-based coordinates also both influence the leftward bias; however their relative contributions are unknown as similar spatial conditions are often collapsed across. More left-side collisions emerged on a route following task in the lower visual field and more right-side collisions were seen in the upper visual field (Thomas, Stuckel, Gutwin, & Elias, 2009). Left-handers made more right-side collisions in the central condition, whereas right-handers showed no bias. Leftward biases on the greyscales task were stronger in the lower visual field; however no distance-based differences were observed (Thomas & Elias, 2010). A stronger spatial bias was found on the greyscales task, whereas a stronger object-based bias was found on the object luminosity task (Thomas & Elias, in press). When individual spatial conditions were examined, the image chosen most often was always located in the lower field. Stimulus type and spatial location interacted to determine which coordinate type contributes more strongly to leftward biases. We also found that the leftward bias on the greyscales task was stronger in the lower visual field during prolonged presentation and in the upper visual field during brief presentation. A global motion task was created to preferentially engage magnocellular projections to the dorsal stream. Isoluminant red/green and blue/yellow colour tasks, which preferentially engage parvocellular projections to the ventral stream, were also created. Leftward biases were seen on the greyscales and motion tasks. On an isoluminant colour task, biases were significantly weakened, suggesting leftward biases exhibited by neurologically normal people are mediated by magnocellular projections to the dorsal stream and this preferential processing leads to a lower visual field advantage on the greyscales task.

Practice of architecture requires the performance of different kind of activities for the production of an architectural work. Architectural production is achieved through two major processes which are design and construction. Each involves activities peculiar to it. Conceptualizing and drawing are two examples of activities embedded in the design process. Generally, there is a time interval between design and construction, in that what is created is not realized immediately. Although there are time intervals between each process and each activity, they must somehow be related. The conventional view of architecture relates them with the aid of analogies or knowledge from socio-political framework. However, these methods divert architecture from questioning issues of the discipline itself. This thesis claims that architecture should be liberated from narratives that are used to relate design, built work and users. Moreover, it suggests that each activity takes shape not through reference to analogies or representations, but through acts at the instant of production. This thesis discusses the acts involved in design process. It claims that design requires the design of its acts as well. For that, it offers ideas about the identification and operation of acts in design with reference to certain works of architecture. The investigation concerning how acts are organized opens up a new area of research in the architectural discipline: a research concerning designography in architecture.

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Neurologically normal individuals show a leftward spatial bias and tend to collide with objects on the right side more frequently than on the left. The upper visual field is associated with extrapersonal space, and mediated by the ventral stream through parvocellular projections. The lower visual field is associated with peripersonal space, and mediated by the dorsal stream through magnocellular projections. Upper and lower visual field differences have been observed in perceptual asymmetries but results have been mixed. Object- and space-based coordinates also both influence the leftward bias; however their relative contributions are unknown as similar spatial conditions are often collapsed across. More left-side collisions emerged on a route following task in the lower visual field and more right-side collisions were seen in the upper visual field (Thomas, Stuckel, Gutwin, & Elias, 2009). Left-handers made more right-side collisions in the central condition, whereas right-handers showed no bias. Leftward biases on the greyscales task were stronger in the lower visual field; however no distance-based differences were observed (Thomas & Elias, 2010). A stronger spatial bias was found on the greyscales task, whereas a stronger object-based bias was found on the object luminosity task (Thomas & Elias, in press). When individual spatial conditions were examined, the image chosen most often was always located in the lower field. Stimulus type and spatial location interacted to determine which coordinate type contributes more strongly to leftward biases. We also found that the leftward bias on the greyscales task was stronger in the lower visual field during prolonged presentation and in the upper visual field during brief presentation. A global motion task was created to preferentially engage magnocellular projections to the dorsal stream. Isoluminant red/green and blue/yellow colour tasks, which preferentially engage parvocellular projections to the ventral stream, were also created. Leftward biases were seen on the greyscales and motion tasks. On an isoluminant colour task, biases were significantly weakened, suggesting leftward biases exhibited by neurologically normal people are mediated by magnocellular projections to the dorsal stream and this preferential processing leads to a lower visual field advantage on the greyscales task.