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 característiques 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 características 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