12 research outputs found
Comparison of Effective Coverage Calculation Methods for Image Quality Assessment Databases
This article provides a comparison of a three methods that can be used for calculating effective coverage of image quality assessment database. The aim of this metric is to show how well the database is filled with variety of images. Foreach image in the database the Spatial Information (SI) and Colorfulness (CF) metric is calculated. The area of convex hull containing all the points on SI x CF plane is indication of total coverage of the database, but it does not show how efficiently this area is utilized. For this purpose an effective coverage was introduced. An analysis is performed for 16 databases - 13 publicaly available and 3 artificial created for the purpose of showing advantages of the effective coverage
Image Processing Using FPGAs
This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs
Investigation of 3DP technology for fabrication of surgical simulation phantoms
The demand for affordable and realistic phantoms for training, in
particular for functional endoscopic sinus surgery (FESS), has continuously
increased in recent years. Conventional training methods, such as current
physical models, virtual simulators and cadavers may have restrictions,
including fidelity, accessibility, cost and ethics.
In this investigation, the potential of three-dimensional printing for the
manufacture of biologically representative simulation materials for surgery
training phantoms has been investigated. A characterisation of sinus anatomical
elements was performed through CT and micro-CT scanning of a cadaveric
sinus portion. In particular, the relevant constituent tissues of each sinus region
have been determined. Secondly, feedback force values experienced during
surgical cutting have been quantified with an actual surgical instrument,
specifically modified for this purpose. Force values from multiple post-mortem
subjects and different areas of the paranasal sinuses have been gathered and
used as a benchmark for the optimisation of 3D-printing materials.
The research has explored the wide range of properties achievable in
3DP through post-processing methods and variation of printing parameters. For
this latter element, a machine-vision system has been developed to monitor the
3DP in real time. The combination of different infiltrants allowed the
reproduction of force values comparable to those registered from cadaveric
human tissue. The internal characteristics of 3D printed samples were shown to
influence their fracture behaviour under resection. Realistic appearance under
endoscopic conditions has also been confirmed.
The utilisation of some of the research has also been demonstrated in
another medical (non-surgical) training application.
This investigation highlights a number of capabilities, and also limitations,
of 3DP for the manufacturing of representative materials for application in
surgical training phantoms
Contributions to region-based image and video analysis: feature aggregation, background subtraction and description constraining
Tesis doctoral inédita leÃda en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de TecnologÃa Electrónica y de las Comunicaciones. Fecha de lectura: 22-01-2016Esta tesis tiene embargado el acceso al texto completo hasta el 22-07-2017The use of regions for image and video analysis has been traditionally motivated by their ability
to diminish the number of processed units and hence, the number of required decisions. However,
as we explore in this thesis, this is just one of the potential advantages that regions may
provide. When dealing with regions, two description spaces may be differentiated: the decision
space, on which regions are shaped—region segmentation—, and the feature space, on which
regions are used for analysis—region-based applications—. These two spaces are highly related.
The solutions taken on the decision space severely affect their performance in the feature space.
Accordingly, in this thesis we propose contributions on both spaces. Regarding the contributions
to region segmentation, these are two-fold. Firstly, we give a twist to a classical region segmentation
technique, the Mean-Shift, by exploring new solutions to automatically set the spectral
kernel bandwidth. Secondly, we propose a method to describe the micro-texture of a pixel
neighbourhood by using an easily customisable filter-bank methodology—which is based on the
discrete cosine transform (DCT)—. The rest of the thesis is devoted to describe region-based
approaches to several highly topical issues in computer vision; two broad tasks are explored:
background subtraction (BS) and local descriptors (LD). Concerning BS, regions are here used
as complementary cues to refine pixel-based BS algorithms: by providing robust to illumination
cues and by storing the background dynamics in a region-driven background modelling. Relating
to LD, the region is here used to reshape the description area usually fixed for local descriptors.
Region-masked versions of classical two-dimensional and three-dimensional local descriptions are
designed. So-built descriptions are proposed for the task of object identification, under a novel
neural-oriented strategy. Furthermore, a local description scheme based on a fuzzy use of the
region membership is derived. This characterisation scheme has been geometrically adapted to
account for projective deformations, providing a suitable tool for finding corresponding points
in wide-baseline scenarios. Experiments have been conducted for every contribution, discussing
the potential benefits and the limitations of the proposed schemes. In overall, obtained results
suggest that the region—conditioned by successful aggregation processes—is a reliable and
useful tool to extrapolate pixel-level results, diminish semantic noise, isolate significant object
cues and constrain local descriptions. The methods and approaches described along this thesis
present alternative or complementary solutions to pixel-based image processing.El uso de regiones para el análisis de imágenes y secuencias de video ha estado tradicionalmente
motivado por su utilidad para disminuir el número de unidades de análisis y, por ende, el número
de decisiones. En esta tesis evidenciamos que esta es sólo una de las muchas ventajas adheridas
a la utilización de regiones. En el procesamiento por regiones deben distinguirse dos espacios de
análisis: el espacio de decisión, en donde se construyen las regiones, y el espacio de caracterÃsticas,
donde se utilizan. Ambos espacios están altamente relacionados. Las soluciones diseñadas para
la construcción de regiones en el espacio de decisión definen su utilidad en el espacio de análisis.
Por este motivo, a lo largo de esta tesis estudiamos ambos espacios. En particular, proponemos
dos contribuciones en la etapa de construcción de regiones. En la primera, revisitamos una
técnica clásica, Mean-Shift, e introducimos un esquema para la selección automática del ancho
de banda que permite estimar localmente la densidad de una determinada caracterÃstica. En
la segunda, utilizamos la transformada discreta del coseno para describir la variabilidad local
en el entorno de un pÃxel. En el resto de la tesis exploramos soluciones en el espacio de caracterÃsticas,
en otras palabras, proponemos aplicaciones que se apoyan en la región para realizar
el procesamiento. Dichas aplicaciones se centran en dos ramas candentes en el ámbito de la
visión por computador: la segregación del frente por substracción del fondo y la descripción
local de los puntos de una imagen. En la rama substracción de fondo, utilizamos las regiones
como unidades de apoyo a los algoritmos basados exclusivamente en el análisis a nivel de pÃxel.
En particular, mejoramos la robustez de estos algoritmos a los cambios locales de iluminación y
al dinamismo del fondo. Para esta última técnica definimos un modelo de fondo completamente
basado en regiones. Las contribuciones asociadas a la rama de descripción local están centradas
en el uso de la región para definir, automáticamente, entornos de descripción alrededor
de los puntos. En las aproximaciones existentes, estos entornos de descripción suelen ser de
tamaño y forma fija. Como resultado de este procedimiento se establece el diseño de versiones
enmascaradas de descriptores bidimensionales y tridimensionales. En el algoritmo desarrollado,
organizamos los descriptores asà diseñados en una estructura neuronal y los utilizamos para la
identificación automática de objetos. Por otro lado, proponemos un esquema de descripción
mediante asociación difusa de pÃxeles a regiones. Este entorno de descripción es transformado
geométricamente para adaptarse a potenciales deformaciones proyectivas en entornos estéreo donde las cámaras están ampliamente separadas. Cada una de las aproximaciones desarrolladas
se evalúa y discute, remarcando las ventajas e inconvenientes asociadas a su utilización. En
general, los resultados obtenidos sugieren que la región, asumiendo que ha sido construida de
manera exitosa, es una herramienta fiable y de utilidad para: extrapolar resultados a nivel de
pixel, reducir el ruido semántico, aislar las caracterÃsticas significativas de los objetos y restringir
la descripción local de estas caracterÃsticas. Los métodos y enfoques descritos a lo largo de esta
tesis establecen soluciones alternativas o complementarias al análisis a nivel de pÃxelIt was partially supported by the Spanish Government trough
its FPU grant program and the projects (TEC2007-65400 - SemanticVideo), (TEC2011-25995 Event
Video) and (TEC2014-53176-R HAVideo); the European Commission (IST-FP6-027685 - Mesh); the
Comunidad de Madrid (S-0505/TIC-0223 - ProMultiDis-CM) and the Spanish Administration Agency
CENIT 2007-1007 (VISION)