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Publications

Publications by Aurélio Campilho

2010

Image Analysis and Recognition, 7th International Conference, ICIAR 2010, Póvoa de Varzim, Portugal, June 21-23, 2010. Proceedings, Part I

Authors
Campilho, AC; Kamel, MS;

Publication
ICIAR (1)

Abstract

1991

3-D DATA ACQUISITION USING THE RATIO OF 2 INTENSITY IMAGES

Authors
SILVA, JA; CAMPILHO, AJC; DOSSANTOS, JCM;

Publication
6TH MEDITERRANEAN ELECTROTECHNICAL CONFERENCE, PROCEEDINGS VOLS 1 AND 2

Abstract
Important aspects of the implementation and calibration of a 3-D data acquisition system based on the ratio of two intensity images are described. These two images are obtained by illuminating the scene with a projector whose light is filtered, successively, by a graded and a constant neutral density filter. Calibration steps, involving the determination of camera and light projector geometric parameters and ratio calibration data, are analyzed. A new ratio calibration procedure is proposed. Results of two depth calculation methods are presented, and system accuracy is evaluated for several test scenes.

2000

Estimating motion flow field in image sequences using Cellular Neural Networks

Authors
Rubin, S; Milanova, M; Campilho, A;

Publication
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED PROCESSING TECHNIQUES AND APPLICATIONS, VOLS I-V

Abstract
In this paper, we present a new algorithm for motion flow field estimation using Cellular Neural Networks (CNN). We start from a mathematical viewpoint (i.e. statistical regularisation based on Markov Random Field (MRF) and proceed by mapping the algorithm onto a cellular neural network. Because of the temporal dynamics inherent in the cells of the CNN it is well suited to processing time-varying images. A robust motion estimation algorithm is achieved by using a spatio-temporal neighbourhood for modelling pixel interactions.

2007

Image segmentation using region merging combined with a multi-class spectral method

Authors
Monteiro, FC; Campilho, A;

Publication
Proceedings of IAPR Conference on Machine Vision Applications, MVA 2007

Abstract
In this paper we propose an image segmentation algorithm that combines region merging with spectral-based techniques. An initial partitioning of the image into primitive regions is produced by applying a region merging approach which produces a chunk graph that takes in attention the image gradient magnitude. This initial partition is the input to a computationally efficient region segmentation process that produces the final segmentation. The latter process uses a multi-class partition that minimizes the normalized cut value for the region graph. We have efficiently applied the proposed approach with good visual and objective segmentation quality results.

2011

Dynamic programming and fuzzy classification for the automatic segmentation of the carotid in ultrasound images

Authors
Rocha, R; Silva, J; Campilho, A;

Publication
Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

Abstract
A new approach is proposed for the automatic detection of the near-end and far-end intima and adventitia inner boundaries in ultrasound images of the common carotid artery. This method uses the instantaneous coefficient of variation edge detector, fuzzy classification of edges, several discriminating features of the carotid wall boundaries and dynamic programming. The carotid wall boundaries are detected both in healthy and in atherosclerotic arteries, with a wide range of plaque types and sizes. Manual and automatic results are significantly better for the far-end wall, where the automatic detection shows an accuracy similar to manual detections. The application of this approach in clinical practice is encouraged by the results for the far-end wall and the short computation time.

2004

Automatic delimitation of lung fields on chest radiographs

Authors
Mendonca, AM; da Silva, JA; Campilho, A;

Publication
2004 2ND IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1 and 2

Abstract
The purpose of the research herein presented is the automatic delimitation of lung fields in posterior-anterior digital chest radiographs. In a computer-aided diagnosis system the precise location of the lungs is important as it allows the reduction of the re-ion under analysis, decreasing the computation time and facilitating data compression. Furthermore, it allows the delimitation of the search area, easing the selective tuning of the abnormalities detection algorithms. The results produced by the automatic method were validated by comparison with manual contours traced by experienced radiologists. Two programs with friendly interfaces were developed for this purpose.

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