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001
Publications

2019

Development of an image-based system to assess agricultural fertilizer spreader pattern

Authors
Marcal, ARS; Cunha, M;

Publication
COMPUTERS AND ELECTRONICS IN AGRICULTURE

Abstract
An Automatic Calibration of Fertilizers (ACFert) system was developed, for use with centrifugal, pendulum or other types of broadcast spreaders which distribute dry granular agricultural materials on the top of the soil. The ACfert is based on image processing techniques and includes a specially designed mat, which should be placed in the ground for spreaders calibration. A set of images acquired outdoor by a standard device (simple camera) is used to extract information about the spreader distribution pattern. Each image is processed independently, providing as output two numerical values for each grid element present in the image - the number of fertilizers/seeds counted, and its numerical label. The performance of ACFert was evaluated for automatic granules detection using a set of manual counting measurements of nitrate fertilizer and wheat seeds. A total of 185 images acquired with two mobiles devices were used with a total of 498 quadrilateral elements observed and analysed. The overall mean absolute relative error between counting and computed by the ACFert system, were 0.75 +/- 0.75% for fertilizer and 2.12 +/- 1.68% for wheat. This near real-time calibration tool is a very low cost system that can be easily used on field, providing results to support accurate spreader calibration in near real time for different types of fertilizers or seeds.

2019

Automatic classification of coral images using colour and textures

Authors
Caridade, CMR; Marcal, ARS;

Publication
CEUR Workshop Proceedings

Abstract
The purpose of this work is to address the imageCLEF 2019 coral challenge - to develop a system for the detection and identification of substrates in coral images. Initially a revision of the 13 classes was carried out by identifying a number of sub-classes for some substrates. Four features were considered - 3 related to greyscale intensity (1) and texture (2), and 1 related to the colour content. The Breiman's Random forest algorithm was used to classify the corals in one of 13 classes defined. A classification accuracy of about 49% was obtained.

2019

Image Based Estimation of Fruit Phytopathogenic Lesions Area

Authors
Marcal, ARS; Santos, EMDS; Tavares, F;

Publication
Pattern Recognition and Image Analysis - Lecture Notes in Computer Science

Abstract

2019

Modified DBSCAN Algorithm for Microscopic Image Analysis of Wood

Authors
Martins, ALR; Marcal, ARS; Pissarra, J;

Publication
Pattern Recognition and Image Analysis - Lecture Notes in Computer Science

Abstract

2018

Automatic identification of pollen in microscopic images

Authors
Santos, EMDS; Marcal, ARS;

Publication
Lecture Notes in Computational Vision and Biomechanics

Abstract
A system for the identification of pollen grains in bright-field microscopic images is presented in this work. The system is based on segmentation of raw images and binary classification for 3 types of pollen grain. The segmentation method developed tackles a major difficulty of the problem: the existence of clustered pollen grains in the initial binary images. Two different SVM classification kernels are compared to identify the 3 pollen types. The method presented in this paper is able to provide a good estimate of the number of pollen grains of Olea Europea (relative error of 1.3%) in microscopic images. For the two others pollen types tested (Corylus and Quercus), the results were not as good (relative errors of 14.5% and 20.3%, respectively). © 2018, Springer International Publishing AG.

Supervised
thesis

2017

Análise Automática de Imagens Pulmonares de Tomografia Computorizada

Author
Susana Augusta Cardoso Leal Lopes

Institution
UP-FCUP

2017

Reconhecimento Automático de Sinais de Trânsito em Imagens Digitais

Author
Moisés Vungo

Institution
UP-FCUP

2015

Visão Computacional para veículos aéreos não tripulados (UAV)

Author
Mónica Cristina Gandra da Rocha Salgado

Institution
UP-FCUP

2015

Elaboração de um método semiautomático para detecção do tecido adiposo epicárdico em Imagens de Ressonância Magnética

Author
Cristiana Sofia dos Santos Machado de Araújo

Institution
UP-FCUP