Análisis de media de diferencia entre imágenes y su posterior implementación usando Matlab

El proyecto consta de dos partes principales y dos anexos. La primera es teórica, en ella realizamos; a modo de introducción, un estudio sobre el tratamiento digital de la imagen, desarrollando las principales técnicas de tratamiento y análisis de imágenes que pudimos estudiar durante la carrera. Una vez desgranado el análisis nos centraremos en la correlación digital de imagen, su evolución y distintas técnicas, donde nos centramos en la correlación cruzada normalizada que usamos posteriormente para la correlación de imágenes con Matlab. La segunda parte consiste en la implementación de un sencillo programa mediante Matlab en el que podremos evaluar y analizar las diferencias entre dos o más imágenes, pudiendo observar gráficamente la desviación en milímetros entre varias imágenes y su dirección con vectores. Posteriormente analizamos los resultados obtenidos y proponemos posibles mejoras para futuros proyectos de correlación de imágenes digitales. Por último, incluimos un par de anexos en los que incluimos un tutorial para automatizar acciones con Adobe Photoshop para facilitar el pretratamiento de fotografías antes de analizarlas con el script y una posible práctica de laboratorio para futuros alumnos de la escuela utilizando nuestro script de Matlab. ABSTRACT. The project involves two main parts and two annexes. The first is theoretical, it performed; by way of introduction, a study on digital image processing, developing the main treatment techniques and image analysis we were able to study along our career. Once shelled analysis we will focus on digital image correlation, evolution and different techniques, where we focus on normalized cross-correlation which we use later for the correlation of images with Matlab. The second part is the implementation of a simple program using Matlab where we can evaluate and analyze the differences between two or more images and can graphically see the deviation in millimeters between various images and their direction vectors. Then we analyze the results and propose possible improvements for future projects correlation of digital images. Finally, we have a couple of annexes in which we include a tutorial to automate actions with Adobe Photoshop to facilitate pretreatment photographs before analyzing the script and a possible lab for future school students using our Matlab script.

Use of subpixel techniques in pocket cameras to measure vibrations and displacements

Presentación oral SPIE Photonics Europe, Brussels, 16-19 April 2012.

Automated digital mosaicking of airborne videography /

"FHTET 96-12."

Improved Techniques for Video Compression and Communication

Thesis (Ph.D.)--University of Washington, 2016-06

Remote sensing applied to slope stability in mountainous roads in Iran

The Alborz Mountain range separates the northern part of Iran from the southern part. It also isolates a narrow coastal strip to the south of the Caspian Sea from the Central Iran plateau. Communication between the south and north until the 1950's was via two roads and one rail link. In 1963 work was completed on a major access road via the Haraz Valley (the most physically hostile area in the region). From the beginning the road was plagued by accidents resulting from unstable slopes on either side of the valley. Heavy casualties persuaded the government to undertake major engineering works to eliminate ''black spots" and make the road safe. However, despite substantial and prolonged expenditure the problems were not solved and casualties increased steadily due to the increase in traffic using the road. Another road was built to bypass the Haraz road and opened to traffic in 1983. But closure of the Haraz road was still impossible because of the growth of settlements along the route and the need for access to other installations such as the Lar Dam. The aim of this research was to explore the possibility of applying Landsat MSS imagery to locating black spots along the road and the instability problems. Landsat data had not previously been applied to highway engineering problems in the study area. Aerial photographs are better in general than satellite images for detailed mapping, but Landsat images are superior for reconnaissance and adequate for mapping at the 1 :250,000 scale. The broad overview and lack of distortion in the Landsat imagery make the images ideal for structural interpretation. The results of Landsat digital image analysis showed that certain rock types and structural features can be delineated and mapped. The most unstable areas comprising steep slopes, free of vegetation cover can be identified using image processing techniques. Structural lineaments revealed from the image analysis led to improved results (delineation of unstable features). Damavand Quaternary volcanics were found to be the dominant rock type along a 40 km stretch of the road. These rock types are inherently unstable and partly responsible for the difficulties along the road. For more detailed geological and morphological interpretation a sample of small subscenes was selected and analysed. A special developed image analysis package was designed at Aston for use on a non specialized computing system. Using this package a new and unique method for image classification was developed, allowing accurate delineation of the critical features of the study area.

Projection and interpolation based techniques for structured and impulsive noise filtering

In this chapter we present the relevant mathematical background to address two well defined signal and image processing problems. Namely, the problem of structured noise filtering and the problem of interpolation of missing data. The former is addressed by recourse to oblique projection based techniques whilst the latter, which can be considered equivalent to impulsive noise filtering, is tackled by appropriate interpolation methods.

Intuitive mobile image browsing on a hexagonal lattice

Following miniaturisation of cameras and their integration into mobile devices such as smartphones combined with the intensive use of the latter, it is likely that in the near future the majority of digital images will be captured using such devices rather than using dedicated cameras. Since many users decide to keep their photos on their mobile devices, effective methods for managing these image collections are required. Common image browsers prove to be only of limited use, especially for large image sets [1].

Image enhancement of real-time television to benefit the visually impaired

Purpose: To examine the use of real-time, generic edge detection, image processing techniques to enhance the television viewing of the visually impaired. Design: Prospective, clinical experimental study. Method: One hundred and two sequential visually impaired (average age 73.8 ± 14.8 years; 59% female) in a single center optimized a dynamic television image with respect to edge detection filter (Prewitt, Sobel, or the two combined), color (red, green, blue, or white), and intensity (one to 15 times) of the overlaid edges. They then rated the original television footage compared with a black-and-white image displaying the edges detected and the original television image with the detected edges overlaid in the chosen color and at the intensity selected. Footage of news, an advertisement, and the end of program credits were subjectively assessed in a random order. Results: A Prewitt filter was preferred (44%) compared with the Sobel filter (27%) or a combination of the two (28%). Green and white were equally popular for displaying the detected edges (32%), with blue (22%) and red (14%) less so. The average preferred edge intensity was 3.5 ± 1.7 times. The image-enhanced television was significantly preferred to the original (P < .001), which in turn was preferred to viewing the detected edges alone (P < .001) for each of the footage clips. Preference was not dependent on the condition causing visual impairment. Seventy percent were definitely willing to buy a set-top box that could achieve these effects for a reasonable price. Conclusions: Simple generic edge detection image enhancement options can be performed on television in real-time and significantly enhance the viewing of the visually impaired. © 2007 Elsevier Inc. All rights reserved.

A Workbench for Document Processing

During the MEMORIAL project time an international consortium has developed a software solution called DDW (Digital Document Workbench). It provides a set of tools to support the process of digitisation of documents from the scanning up to the retrievable presentation of the content. The attention is focused to machine typed archival documents. One of the important features is the evaluation of quality in each step of the process. The workbench consists of automatic parts as well as of parts which request human activity. The measurable improvement of 20% shows the approach is successful.

Application of Fuzzy Logic on Image Edge Detection

In this paper a novel method for an application of digital image processing, Edge Detection is developed. The contemporary Fuzzy logic, a key concept of artificial intelligence helps to implement the fuzzy relative pixel value algorithms and helps to find and highlight all the edges associated with an image by checking the relative pixel values and thus provides an algorithm to abridge the concepts of digital image processing and artificial intelligence. Exhaustive scanning of an image using the windowing technique takes place which is subjected to a set of fuzzy conditions for the comparison of pixel values with adjacent pixels to check the pixel magnitude gradient in the window. After the testing of fuzzy conditions the appropriate values are allocated to the pixels in the window under testing to provide an image highlighted with all the associated edges.

Minimum Mean Square Error Approach in Images Processing for Full-field Displacements and Deformation Measurements

A vision system is applied to full-field displacements and deformation measurements in solid mechanics. A speckle like pattern is preliminary formed on the surface under investigation. To determine displacements field of one speckle image with respect to a reference speckle image, sub-images, referred to Zones Of Interest (ZOI) are considered. The field is obtained by matching a ZOI in the reference image with the respective ZOI in the moved image. Two image processing techniques are used for implementing the matching procedure: – cross correlation function and minimum mean square error (MMSE) of the ZOI intensity distribution. The two algorithms are compared and the influence of the ZOI size on the accuracy of measurements is studied.

Extended principal component analysis and its applications to image analysis

The objectives of this research are to analyze and develop a modified Principal Component Analysis (PCA) and to develop a two-dimensional PCA with applications in image processing. PCA is a classical multivariate technique where its mathematical treatment is purely based on the eigensystem of positive-definite symmetric matrices. Its main function is to statistically transform a set of correlated variables to a new set of uncorrelated variables over $\IR\sp{n}$ by retaining most of the variations present in the original variables.^ The variances of the Principal Components (PCs) obtained from the modified PCA form a correlation matrix of the original variables. The decomposition of this correlation matrix into a diagonal matrix produces a set of orthonormal basis that can be used to linearly transform the given PCs. It is this linear transformation that reproduces the original variables. The two-dimensional PCA can be devised as a two successive of one-dimensional PCA. It can be shown that, for an $m\times n$ matrix, the PCs obtained from the two-dimensional PCA are the singular values of that matrix.^ In this research, several applications for image analysis based on PCA are developed, i.e., edge detection, feature extraction, and multi-resolution PCA decomposition and reconstruction. ^

Three-dimensional brain fiber tracking modeling in diffusion tensor imaging

This dissertation establishes the foundation for a new 3-D visual interface integrating Magnetic Resonance Imaging (MRI) to Diffusion Tensor Imaging (DTI). The need for such an interface is critical for understanding brain dynamics, and for providing more accurate diagnosis of key brain dysfunctions in terms of neuronal connectivity. ^ This work involved two research fronts: (1) the development of new image processing and visualization techniques in order to accurately establish relational positioning of neuronal fiber tracts and key landmarks in 3-D brain atlases, and (2) the obligation to address the computational requirements such that the processing time is within the practical bounds of clinical settings. The system was evaluated using data from thirty patients and volunteers with the Brain Institute at Miami Children's Hospital. ^ Innovative visualization mechanisms allow for the first time white matter fiber tracts to be displayed alongside key anatomical structures within accurately registered 3-D semi-transparent images of the brain. ^ The segmentation algorithm is based on the calculation of mathematically-tuned thresholds and region-detection modules. The uniqueness of the algorithm is in its ability to perform fast and accurate segmentation of the ventricles. In contrast to the manual selection of the ventricles, which averaged over 12 minutes, the segmentation algorithm averaged less than 10 seconds in its execution. ^ The registration algorithm established searches and compares MR with DT images of the same subject, where derived correlation measures quantify the resulting accuracy. Overall, the images were 27% more correlated after registration, while an average of 1.5 seconds is all it took to execute the processes of registration, interpolation, and re-slicing of the images all at the same time and in all the given dimensions. ^ This interface was fully embedded into a fiber-tracking software system in order to establish an optimal research environment. This highly integrated 3-D visualization system reached a practical level that makes it ready for clinical deployment. ^