Manuel João Oliveira Ferreira

Optic disc detection in color fundus images using ant colony optimization

Diabetic retinopathy has been revealed as the most common cause of blindness among people of working age in developed countries. However, loss of vision could be prevented by an early detection of the disease and, therefore, by a regular screening program to detect retinopathy. Due to its characteristics, the digital color fundus photographs have been the easiest way to analyze the eye fundus. An important prerequisite for automation is the segmentation of the main anatomical features in the image, particularly the optic disc. Currently, there are many works reported in the literature with the purpose of detecting and segmenting this anatomical structure. Though, none of them performs as needed, especially when dealing with images presenting pathologies and a great variability. Ant colony optimization (ACO) is an optimization algorithm inspired by the foraging behavior of some ant species that has been applied in image processing with different purposes. In this paper, this algorithm preceded by anisotropic diffusion is used for optic disc detection in color fundus images. Experimental results demonstrate the good performance of the proposed approach as the optic disc was detected in most of all the images used, even in the images with great variability.

Quantification of total chromium and hexavalent chromium in UHT milk by ETAAS

Procedures for the quantification of total chromium and hexavalent chromium in UHT milk samples are presented. Total chromium was determined directly in milk with the addition of a surfactant and a mixture of Pd and Mg as a chemical modifier. For the selective separation of hexavalent chromium, the sample pre-treatment consisted in precipitation of proteins and elution of the supernatant through a Chromabond NH2 column. The metal was eluted with nitric acid. Both total chromium and hexavalent chromium were evaluated by atomic absorption spectrometry with electrothermal atomization using the same instrumental conditions. The detection limits were 0.2 and 0.15 microgram l-1 for total chromium and hexavalent chromium, respectively. The linearity ranges under the optimized conditions were 0.2-20 and 0.15-50 micrograms l-1. For total chromium the precision was 4.9 and 5.7% for the analytical and the over-all procedure, respectively, and for hexavalent chromium 4.3 and 4.9%, respectively. The validation of both procedures was performed by the standard additions method and the recoveries were higher than 93% in all cases. For total chromium, a certified reference material was also used to validate the methodology. The methods were applied to the determination of total chromium and hexavalent chromium in 60 UHT milk samples.

Exudate segmentation in fundus images using an ant colony optimization approach

The leading cause of new blindness and vision defects in working-age people, diabetic retinopathy is a serious public health problem in developed countries. Automatic identification of diabetic retinopathy lesions, such as exudates, in fundus images can contribute to early diagnosis. Currently, many studies in the literature have reported on segmenting exudates, but none of the methods performs as needed. Moreover, several approaches were tested in independent databases, and the approachs capacity to generalize was not proved. The present study aims to segment exudates with a new unsupervised approach based on the ant colony optimization algorithm. The algorithms performance was evaluated with a dataset available online, and the experimental results showed that this algorithm performs better than the traditional Kirsch filter in detecting exudates.

Applications of simple robots to encourage social receptiveness of adolescents with autism

This paper reports the preliminary research studies regarding the use of LEGO Mindstorms TM robots as a therapy for autistic young people. Most autistic people hardly communicate in a social environment, living in their own world. This is the first step in a broader project which aims to improve the autistic people social life and also their ability to communicate, using the robot as a social bridge between them and the surrounding environment/people. The target group is 17-19 years old having autism disorder and developmental disability. The trials consists of undemanding plays where the intervention of the autistic person is required, using simple inputs, such as voice commands, pressing a button or clapping hands. The presented work intends to evaluate the reaction of this particular target group to the introduction of a toy-like robot in their classroom daily life. The methodology applied, the detailed description as well as the analysis of the experiments are presented and discussed.

Variability in phenolic composition of Hypericum androsaemum.

The methanolic extracts of fifteen Hypericum androsaemum samples, growing spontaneously or cultivated in Portugal, were analysed by HPLC/DAD, allowing the identification of 9 phenolic compounds and the detection of 6 phloroglucinols. Total amounts of phenolics found ranged from 11 to 39 g/kg, and the influence of some factors which may be responsible for this variation is discussed. The individual compounds were also quantified. Four different phenolic profiles were found concerning both qualitative and quantitative composition, indicating the possible existence of chemical polymorphism.

An approach to promote social and communication behaviors in children with autism spectrum disorders: Robot based intervention

Most autistic people present some difficulties in developing social behavior, living in their own world. This study has the goal to improve the social life of children with autism with a main focus in promoting their social interaction and communication. It is necessary to call for childrens attention and enforce their collaboration, where a robot, LEGO MindStorm, behaves as a mediator/promoter of this interaction. A set of experiments designed to share objects and fulfill simple orders, by the 11 years old autistic child at the time of daily routine work and in-game with the robot, are described. The generalization of the acquired skills by the child in new contexts and environments are also tested. Results are described showing the outcomes of the experiments.

Fast correction of lens distortion for image applications

The main use of video cameras in industrial applications regards to detection of defects and noncontact measuring. If the first case is usually a problem of mismatching between two images, the absolute position being nonimportant, the second relies on accurate proportional correspondence between image and object dimensions. In the usual set-up, the object is mainly flat and its image is obtained using a video camera whose lens axis is orthogonal and centred relative to the object. The co-ordinate system of the object should be ideally related to that of the image by a simple translation and change of scale, once an initial mechanical rotation adjustment of the set-up is made. The geometric distortions, mainly pincushion and barrel types, must be either avoided, using a well corrected lens in a proper set-up, or corrected through digital image processing techniques. The use of an acceptable lens imposes a higher price or restrictions to the angle of view, as wide angles are harder to correct acceptably. When space limitations are important and a wide angle is sought, an expensive lens and/or time consuming correcting algorithms are mandatory. The proposed algorithm builds a correction table for the set-up in use, which remains fairly constant in industrial applications. This table divides the image in regions. For each region the correction can be put as a single delta-x/delta-y translation of the included pixels. This can be done fairly quickly when compared to the general morphing algorithms.

Multi-objective parameter CPG optimization for gait generation of a quadruped robot considering behavioral diversity

This paper presents a gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm. CPGs are modeled as autonomous differential equations, that generate the necessary limb movement to perform the required walking gait. In order to optimize the walking gait, four conflicting objectives are considered, simultaneously: minimize the body vibration, maximize the velocity, maximize the wide stability margin and maximize the behavioral diversity. The results of NSGA-II for this multi-objective problem are discussed. The effect of the inclusion of a behavioral diversity objective in the system is also studied in terms of the walking gait achieved. The experimental results show the effectiveness of this multi-objective approach. The several walking gait solutions obtained correspond to different trade-off between the objectives.

Cork Parquet Quality Control Vision System Based on Texture Segmentation and Fuzzy Grammar

This paper presents a quality control vision system developed for the inspection of cork parquets that is already applied in the Portuguese cork industry. It is devoted specifically to the most critical quality issues: visibility of the lowest layer (BASE) on the noble layer (UPPER) and the homogeneity of this noble layer. Since these aspects are related with the texture of the raw material, the system was based on texture segmentation techniques. Features used were extracted from detail images of the wavelet transform. The classifier consists of a fuzzy grammar inference system. The segmentation procedure revealed a good performance indicated by high classification rates. Behavior in the industrial environment has been demonstrating high performance, revealing good perspectives for full spread industrialization.

Using a multi-agent system approach for microaneurysm detection in fundus images

OBJECTIVE Microaneurysms represent the first sign of diabetic retinopathy, and their detection is fundamental for the prevention of vision impairment. Despite several research attempts to develop an automated system to detect microaneurysms in fundus images, none has shown the level of performance required for clinical practice. We propose a new approach, based on a multi-agent system model, for microaneurysm segmentation. METHODS AND MATERIALS A multi-agent based approach, preceded by a preprocessing phase to allow construction of the environment in which agents are situated and interact, is presented. The proposed method is applied to two available online datasets and results are compared to other previously described approaches. RESULTS Microaneurysm segmentation emerges from agent interaction. The final score of the proposed approach was 0.240 in the Retinopathy Online Challenge. CONCLUSIONS We achieved competitive results, primarily in detecting microaneurysms close to vessels, compared to more conventional algorithms. Despite these results not being optimum, they are encouraging and reveal that some improvements may be made.