84 research outputs found
Detector de contorns basat en el domini transformat
RESUM
En aquest document es presenta un detector de contorns d’imatges basat en el domini transformat. A partir de la
interpretació de la transformada de Fourier de la imatge i la seva formulació matricial en termes dels diferents modes,
es realitza una selecció de les components passa baixes a partir de les quals es reconstrueix la component de baixa
freqüència que es resta de la imatge original per tal d’obtenir el detector. Aquest detector de contorns no és esbiaixat.
L’algorisme pot ser aplicat utilitzant diferents mides del bloc de processament, que pot anar de la imatge sencera a
blocs de reduïdes dimensions: 36X36, 16x16 o 8x8, per fer un seguiment de les propietats locals de la imatge quan
aquesta és presenta caracterÃstiques espacials poc uniformes.En este documento se presenta un detector de contornos de imágenes basado en el dominio transformado. A partir de
la interpretación de la transformada de Fourier de la imagen y su formulación matricial en términos de los diferentes
modos, se realiza una selección de las componentes paso-bajas a partir de las cuales se reconstruye la componente
de baja frecuencia que se restará a la imagen original pora obtener el detector. Este detector de contornos no es
sesgado. El algoritmo puede ser aplicado utilizando diferentes medidas del bloque de procesado, que puede ir de la
imagen entera a bloques de reducidas dimensiones: 36x36, 16x16 o 8x8, que permiten hacer un seguimiento de las
propiedades locales de la imagen cuando ésta presenta caracterÃsticas sectoriales muy diversas.In this document an image contour detector based on the transformed domain is presented. Following the interpretation
of the image Fourier transform and its matrix formulation in terms of its different modes, we select the base-band ones
from which we reconstruct the low frequency image component. This component is subtracted to the original image in
order to obtain the contours. This contour detector is not biased. The algorithm can be implemented using different block
processing sizes, which can range from the entire image to blocks of smaller dimensions: 36x36, 16x16 or 8x8. Small
blocks improve the contour detector performance when the local properties of the image are not uniform
New FFT/IFFT Factorizations with Regular Interconnection Pattern Stage-to-Stage Subblocks
Les factoritzacions de la FFT (Fast Fourier Transform) que presenten un patró d’interconnexió regular entre factors o
etapes son conegudes com algorismes paral·lels, o algorismes de Pease, ja que foren originalment proposats per
Pease. En aquesta contribució s’han desenvolupat noves factoritzacions amb blocs que presenten el patró
d’interconnexió regular de Pease. S’ha mostrat com aquests blocs poden ser obtinguts a una escala prèviament
seleccionada. Les noves factoritzacions per ambdues FFT i IFFT (Inverse FFT) tenen dues classes de factors: uns pocs
factors del tipus Cooley-Tukey i els nous factors que proporcionen la mateix patró d’interconnexió de Pease en blocs.
Per a una factorització donada, els blocs comparteixen dimensions, el patró d’interconnexió etapa a etapa i a més cada
un d’ells pot ser calculat independentment dels altres.FFT (Fast Fourier Transform) factorizations presenting a regular interconnection pattern between factors or stages are
known as parallel algorithms, or Pease algorithms since were first proposed by Pease. In this paper, new FFT/IFFT
(Inverse FFT) factorizations with blocks that exhibit regular Pease interconnection pattern are derived. It is shown these
blocks can be obtained at a previously selected scale. The new factorizations for both the FFT and IFFT have two kinds
of factors: a few Cooley-Tukey type factors and new factors providing the same Pease interconnection pattern property
in blocks. For a given factorization, these blocks share dimensions, the interconnection pattern stage-to-stage, and all of
them can be calculated independently from one another.Las factoritzaciones de la FFT (Fast Fourier Transform) que presentan un patrón de interconexiones regular entre
factores o etapas son conocidas como algoritmos paralelos, o algoritmos de Pease, puesto que fueron originalmente
propuestos por Pease. En esta contribución se han desarrollado nuevas factoritzaciones en subbloques que presentan
el patrón de interconexión regular de Pease. Se ha mostrado como estos bloques pueden ser obtenidos a una escalera
previamente seleccionada. Las nuevas factoritzaciones para ambas FFT y IFFT (Inverse FFT) tienen dos clases de
factores: unos pocos factores del tipo Cooley-Tukey y los nuevos factores que proporcionan el mismo patrón de
interconexión de Pease en bloques. Para una factoritzación dada, los bloques comparten dimensiones, patrón
d’interconexión etapa a etapa y además cada uno de ellos puede ser calculado independientemente de los otros
Two Families of Radix-2 FFT Algorithms With Ordered Input and Output Data
Two radix-2 families of fast Fourier transform (FFT)
algorithms that have the property that both inputs and outputs
are addressed in natural order are derived in this letter. The algorithms
obtained have the same complexity that Cooley–Tukey
radix-2 algorithms but avoid the bit-reversal ordering applied to
the input. These algorithms can be thought as a variation of the
radix-2 Cooley–Tukey ones
Parameterization of written signatures based on EFD
In this work we propose a method to quantify written signatures from digitalized images based on the use of
Elliptical Fourier Descriptors (EFD). As usually signatures are not represented as a closed contour, and
being that a necessary condition in order to apply EFD, we have developed a method that represents the
signatures by means of a set of closed contours. One of the advantages of this method is that it can
reconstruct the original shape from all the coefficients, or an approximated shape from a reduced set of them
finding the appropriate number of EFD coefficients required for preserving the important information in
each application. EFD provides accurate frequency information, thus the use of EFD opens many
possibilities. The method can be extended to represent other kind of shapes
Features extraction based on the Discrete Hartley Transform for closed contour
In this paper the authors propose a new closed contour descriptor that could be seen as a Feature Extractor of closed
contours based on the Discrete Hartley Transform (DHT), its main characteristic is that uses only half of the coefficients required
by Elliptical Fourier Descriptors (EFD) to obtain a contour approximation with similar error measure. The proposed closed contour
descriptor provides an excellent capability of information compression useful for a great number of AI applications. Moreover
it can provide scale, position and rotation invariance, and last but not least it has the advantage that both the parameterization
and the reconstructed shape from the compressed set can be computed very efficiently by the fast Discrete Hartley Transform
(DHT) algorithm. This Feature Extractor could be useful when the application claims for reversible features and when the user
needs and easy measure of the quality for a given level of compression, scalable from low to very high quality
Improving Pitch Tracking Performance in Hard Noise Conditions by a Preprocessing Based on Mathematical Morphology
In this paper we show how a nonlinear preprocessing of speech
signal -with high noise- based on morphological filters improves the
performance of robust algorithms for pitch tracking (RAPT). This result
happens for a very simple morphological filter. More sophisticated ones could
even improve such results. Mathematical morphology is widely used in image
processing and has a great amount of applications. Almost all its formulations
derived in the two-dimensional framework are easily reformulated to be
adapted to one-dimensional contex
Exploring Non-linear Transformations for an Entropybased Voice Activity Detector
In this paper we explore the use of non-linear transformations in
order to improve the performance of an entropy based voice activity detector
(VAD). The idea of using a non-linear transformation comes from some
previous work done in speech linear prediction (LPC) field based in source
separation techniques, where the score function was added into the classical
equations in order to take into account the real distribution of the signal. We
explore the possibility of estimating the entropy of frames after calculating its
score function, instead of using original frames. We observe that if signal is
clean, estimated entropy is essentially the same; but if signal is noisy
transformed frames (with score function) are able to give different entropy if
the frame is voiced against unvoiced ones. Experimental results show that this
fact permits to detect voice activity under high noise, where simple entropy
method fails
Satellite image georegistration from coast-line codification
Martech 2007 International Workshop on Marine Technology, 15-16 november 2007, Vilanova i la Geltrú, Spain.-- 2 pages, 3 figuresThis paper presents a contour-based approach for automatic image registration in satellite oceanography. Accurate image georegistration is an essential step to increase the eff ectiveness of all the image processing methods that aggregate information from diff erent sources, i.e. applying data fusion techniques. In our approach the images description is based on main contours extracted from coast-line. Each contour is codifi ed by a modifi ed chain-code, and the result is a discrete value sequence. The classical registration techniques were area-based, and the registration was done in a 2D domain (spatial and/or transformed); this approach is feature-based, and the registration is done in a 1D domain (discrete sequences). This new technique improves the registration results. It allows the registration of multimodal images, and the registration when there are occlusions and gaps in the images (i.e. due to clouds), or the registration on images with moderate perspective changes. Finally, it has to be pointed out that the proposed contour-matching technique assumes that a reference image, containing the coastlines of the input image geographical area, is availablePeer reviewe
Tackling the relevance of packaging in life cycle assessment of virgin olive oil and the environmental consequences of regulation
Production and consumption of olive oil is very important in Europe, being this product a basic element in the Mediterranean diet since long ago. The project objective is two-fold: a study of the contribution of virgin olive oils (VOOs) usual packaging to the whole life cycle of the product and a study of the environmental consequences of the Spanish Government regulation on VOO packaging. A life cycle assessment (LCA) according to ISO 14044 has been performed using the CML methodology for the impact assessment. The results show that the packaging influence varies from 2 to 300%, depending on the impact category and type of packaging (glass, tin or polyethylene terephtalate). Glass, which is related to higher quality perception by consumers, was found to be the most influencing material (due to its weight); however, this impact may be fairly reduced by applying ecodesign strategies (such as weight reduction and recycled-glass percentage increase). A new Spanish regulation on the mandatory use of non-refillable oilers in HORECA establishments (hotels, restaurants and caterings) aims to provide more quality assurance and better information to consumers; however, it was also found to mean a 74% increase in greenhouse gases emissions. This regulation was deeply discussed at European level and its application was withdraw due to consumers rejection, except for Spain. The findings of the present case study show that LCA and ecodesign should be important tools to be promoted and applied in policy making to reduce non-desirable consequences of regulation
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