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Publications

2016

Automatic Cattle Identification Using Graph Matching Based on Local Invariant Features

Authors
Monteiro, FC;

Publication
IMAGE ANALYSIS AND RECOGNITION (ICIAR 2016)

Abstract
Cattle muzzle classification can be considered as a biometric identifier important to animal traceability systems to ensure the integrity of the food chain. This paper presents a muzzle-based classification system that combines local invariant features with graph matching. The proposed approach consists of three phases; namely feature extraction, graph matching, and matching refinement. The experimental results showed that our approach is superior than existing works as ours achieves an all correct identification for the tested images. In addition, the results proved that our proposed method achieved this high accuracy even if the testing images are rotated in various angles.

2016

Automatic tracking and deformation measurements of red blood cells flowing through a microchannel with a microstenosis: the keyhole model

Authors
Taboada, B; Monteiro, FC; Lima, R;

Publication
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION

Abstract
This study aimed to assess the motion and its deformation index (DI) of red blood cells (RBCs) flowing through a microchannel with a microstenosis using an image analysis-based method. For this purpose, a microchannel having a smooth contraction was used and the images were captured by a standard high-speed microscopy system. An automatic image-processing and analysing method was developed in a MATLAB environment to not only track the motion of RBCs but also measure the DI along the microchannel. The keyhole model, tested in this study, proved to be a promising technique to automatically track individual RBCs in microchannels.

2016

Performance analysis of speckle ultrasound image filtering

Authors
Rosa, R; Monteiro, FC;

Publication
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION

Abstract
Over the last three decades, several despeckling filters have been developed by researchers to reduce the speckle noise inherently present in ultrasound B-scan images without losing the diagnostic information. This paper compiles and compares well-known techniques mostly used in the smoothing or suppression of speckle noise in ultrasound images. A comparison of the methods studied is done based on an experiment, using quality metrics, texture analysis and interpretation of profiles to evaluate their performance and show the benefits each one can contribute to denoising and feature preservation. To test the methods, a noise-free image of a kidney is used and then the Field II program simulates a B-mode ultrasound image. By this way, the smoothing techniques can be compared using numeric metrics, taking the noise-free image as a reference. In this study, a total of 17 different speckle reduction algorithms have been documented based on spatial filtering, diffusion filtering and wavelet filtering, with 15 qualitative metrics estimation. We use the tendencies observed in our study in real images. A new evaluation metric is proposed to evaluate the despeckling results.

2014

Visualization of red blood cells flowing through a PDMS microchannel with a microstenosis: An image analysis assessment

Authors
Monteiro, FC; Taboada, B; Lima, R;

Publication
COMPUTATIONAL VISION AND MEDICAL IMAGE PROCESSING IV

Abstract
The present study aims to assess the motion of red blood cells (RBCs) under both shear and extensional flow using an image based technique. For this purpose, a microchannel having a smooth contraction was used and the images were captured by a standard high-speed microscopy system. An image processing and analyzing method has been developed in the MATLAB environment, to track the RBCs motion. The keyhole model, tested in this study, proved to be a promising technique to track individual RBCs in microchannels.

2014

Towards a Comprehensive Evaluation of Ultrasound Speckle Reduction

Authors
Monteiro, FC; Rufino, J; Rufino, J; Cadavez, V; Cadavez, V;

Publication
IMAGE ANALYSIS AND RECOGNITION, ICIAR 2014, PT I

Abstract
Over the last three decades, several despeckling filters have been developed to reduce the speckle noise inherently present in ultrasound images without losing the diagnostic information. In this paper, a new intensity and feature preservation evaluation metric for full speckle reduction evaluation is proposed based contrast and feature similarities. A comparison of the despeckling methods is done, using quality metrics and visual interpretation of images profiles to evaluate their performance and show the benefits each one can contribute to noise reduction and feature preservation. To test the methods, noise-free images and simulated B-mode ultrasound images are used. This way, the despeckling techniques can be compared using numeric metrics, taking the noise-free image as a reference. In this study, a total of seventeen different speckle reduction algorithms have been documented based on adaptive filtering, diffusion filtering and wavelet filtering, with sixteen qualitative metrics estimation.