Cookies
Usamos cookies para melhorar nosso site e a sua experiência. Ao continuar a navegar no site, você aceita a nossa política de cookies. Ver mais
Aceitar Rejeitar
  • Menu
Publicações

Publicações por André Marçal

2013

Global Constraints for Syntactic Consistency in OMR: An Ongoing Approach

Autores
Rebelo, A; Marcal, ARS; Cardoso, JS;

Publicação
IMAGE ANALYSIS AND RECOGNITION

Abstract
Optical Music Recognition (OMR) systems are an indispensable tool to transform the paper-based music scores and manuscripts into a machine-readable symbolic format. A system like this potentiates search, retrieval and analysis. One of the problematic stages is the musical symbols detection where operations to localize and to isolate musical objects are developed. The complexity is caused by printing and digitalization, as well as the paper degradation over time. Distortions inherent in staff lines, broken, connected and overlapping symbols, differences in sizes and shapes, noise, and zones of high density of symbols is even worst when we are dealing with handwritten music scores. In this paper the exploration of an optimization approach to support semantic and syntactic consistency after the music symbols extraction phase is proposed. The inclusion of this ongoing technique can lead to better results and encourage further experiences in the field of handwritten music scores recognition.

2013

Monitoring Vegetation Dynamics Inferred by Satellite Data Using the PhenoSat Tool

Autores
Rodrigues, A; Marcal, ARS; Cunha, M;

Publicação
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Abstract
PhenoSat is an experimental software tool that produces phenological information from satellite vegetation index time series. The main characteristics and functionalities of the PhenoSat tool are presented, and its performance is compared against observed measures and other available software applications. A multiyear experiment was carried out for different vegetation types: vineyard, low shrublands, and seminatural meadows. Temporal satellite normalized difference vegetation index (NDVI) data provided by MODerate resolution Imaging Spectroradiometer and Satellite Pour l'Observation de la Terre VEGETATION were used to test the ability of the software in extracting vegetation dynamics information. Three important PhenoSat features were analyzed: extraction of the main growing season information, estimation of double growth season parameters, and the advantage of selecting a temporal region of interest. Seven noise reduction filters were applied: cubic smoothing splines, polynomial curve fitting, Fourier series, Gaussian models, piecewise logistic, Savitzky-Golay (SG), and a combination of the last two. The results showed that PhenoSat is a useful tool to extract NDVI metrics related to vegetation dynamics, obtaining high significant correlations between observed and estimated parameters for most of the phenological stages and vegetation types studied. Using the combination of SG and piecewise logistic to fit the NDVI time series, PhenoSat obtained correlations higher than 0.71, except for the seminatural meadow start of season. The selection of a temporal region of interest improved the fitting process, consequently providing more reliable phenological information.

2013

PH2 - A dermoscopic image database for research and benchmarking

Autores
Mendonca, T; Ferreira, PM; Marques, JS; Marca, ARS; Rozeira, J;

Publicação
2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)

Abstract
The increasing incidence of melanoma has recently promoted the development of computer-aided diagnosis systems for the classification of dermoscopic images. Unfortunately, the performance of such systems cannot be compared since they are evaluated in different sets of images by their authors and there are no public databases available to perform a fair evaluation of multiple systems. In this paper, a dermoscopic image database, called PH2, is presented. The PH2 database includes the manual segmentation, the clinical diagnosis, and the identification of several dermoscopic structures, performed by expert dermatologists, in a set of 200 dermoscopic images. The PH2 database will be made freely available for research and benchmarking purposes.

2016

PhenoSat – a tool for remote sensing based analysis of vegetation dynamics

Autores
Rodrigues, A; Marcal, ARS; Cunha, M;

Publicação
Remote Sensing and Digital Image Processing

Abstract
PhenoSat is a software tool that extracts phenological information from satellite based vegetation index time-series. This chapter presents PhenoSat and tests its main characteristics and functionalities using a multi-year experiment and different vegetation types – vineyard and semi-natural meadows. Three important features were analyzed: (1) the extraction of phenological information for the main growing season, (2) detection and estimation of double growth season parameters, and (3) the advantages of selecting a sub-temporal region of interest. Temporal NDVI satellite data from SPOT VEGETATION and NOAA AVHRR were used. Six fitting methods were applied to filter the satellite noise data: cubic splines, piecewise-logistic, Gaussian models, Fourier series, polynomial curve-fitting and Savitzky-Golay. PhenoSat showed to be capable to extract phenological information consistent with reference measurements, presenting in some cases correlations above 70% (n=10; p=0.012). The start of in-season regrowth in semi-natural meadows was detected with a precision lower than 10-days. The selection of a temporal region of interest, improve the fitting process (R-square increased from 0.596 to 0.997). This improvement detected more accurately the maximum vegetation development and provided more reliable results. PhenoSat showed to be capable to adapt to different vegetation types, and different satellite data sources, proving to be a useful tool to extract metrics related with vegetation dynamics. © Springer International Publishing AG 2016.

2013

PH2 - A dermoscopic image database for research and benchmarking

Autores
Mendonça, T; Ferreira, PM; Marques, JS; Marçal, ARS; Rozeira, J;

Publicação
35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013, Osaka, Japan, July 3-7, 2013

Abstract

2013

Land cover map production for Brazilian Amazon using NDVI SPOT VEGETATION time series

Autores
Rodrigues, A; Marcal, ARS; Furlan, D; Ballester, MV; Cunha, M;

Publicação
CANADIAN JOURNAL OF REMOTE SENSING

Abstract
Earth Observation Satellite (EOS) data have a great potential for land cover mapping, which is mostly based on high resolution images. However, in tropical areas the use of these images is seriously limited due to the presence of clouds. This paper evaluates the ability of temporal-based image classification methods to produce land cover maps in tropical regions. A new approach is proposed for land cover classification and updating based exclusively on temporal series data, illustrated with a practical test using SPOT VEGETATION satellite images from 1999 to 2011 for Rondonia (Amazon), Brazil. Using the GLC2000 as reference, a Normalized Difference Vegetation Index (NDVI) time series of 15 distinct land cover classes (LCC) were created. Two classifiers were used (Euclidean Distance and Dynamic Time Warping) to produce maps of land cover changes for 1999-2011. Due to the difficulties in discriminating 15 LCC in the Amazon region, a hierarchical aggregation was performed by joining the initial classes gradually up to four broad classes. The land cover changes in the 1999-2011 period were evaluated using criteria based on the classification results for the individual years. The comparison with reference data showed consistent results, proving that this approach is able to produce accurate land cover maps using exclusively temporal series EOS data.

  • 1
  • 5