Indicadores de bem-estar baseados em reações comportamentais de matrizes pesadas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Image analysis for assessing broiler breeder behavior response to thermal environment

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Digital monitoring of broiler breeder behavior for assessment of thermal welfare

The assessment of welfare issues has been a challenge for poultry producers, and lately welfare standards needs to be reached in order to agree with international market demand. This research proposes the use of continuous behavior monitoring in order to contribute for assessing welfare. A software was developed using the language Clarium. The software managed the recording of data as well as the data searching in the database Firebird. Both software and the observational methodology were tested in a trial conducted inside an environmental chamber, using three genetics of broiler breeders. Behavioral pattern was recorded and correlated to ambient thermal and aerial variation. Monitoring video cameras were placed on the roof facing the used for registering the bird's behavior. From video camera images were recorded during the total period when the ambient was bright, and for analyzing the video images a sample of 15min observation in the morning and 15 min in the afternoon was used, adding up to 30 min daily observation. A specific model so-called behavior was developed inside the software for counting specific behavior and its frequency of occurrence, as well as its duration. Electronic identification was recorded for 24h period. Behavioral video recording images was related to the data recorded using electronic identification.. Statistical analysis of data allowed to identify behavioral differences related to the change in thermal environment, and ultimately indicating thermal stress and departure from welfare conditions.

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A new closed-vessel conductively heated digestion system: fostering plant analysis by inductively coupled plasma optical emission spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Quantificação da desintegração de comprimidos por fluxo ótico em seqüências de imagens de biosusceptometria AC

AC Biosusceptometry (ACB) is a low-cost biomagnetic tool that has been successfully applied on pharmaceutical research to evaluate performance of solid dosage forms. The aim of this work was to evaluate the Horn & Shunck method to access tablet disintegration. To evaluate the HS results was record on video a test with a objet moving in a rail with a constant velocity. The desintegration was recorded on video and ACB, which used have seven pairs of detection coils and a pair of excitation coils to mensure the magnetic ux variation. The signals were ampli ed and digitalized to create images, which were restored by Wiener lter, while the video images are converted to gray scale, both are normalized and binarized and had the optical ow estimation calculated by Horn & Schunck (HS) algorithm. All signals and images are processed and developed algorithm on Matlab. During the tests the ve tablets (500mg ferrite, 375mg excipients, compression 10 to 50 kN) were on a becker between of the ACB system and of the video system, and only touching the surface of the water. With all OF maps calculated was realized the sum of the resultants of each, to get a disintegration process resultant for each compression. Whit that was possible observed the disintegration behaves. For the compression force study the HS components of each sequence was sum, take mean and normalized for sequence's max modulo, therefore can be observed a high growing on less compression tablets. We can conclude the HS algorithm is viable to tablets disintegration data collection and whit that was possible to create a tablets disintegration analyzes protocol, which would be useful on desintegration kinetics study

Hybrid visual-driven decision support system in video monitor manufacturing

An intelligent system that emulates human decision behaviour based on visual data acquisition is proposed. The approach is useful in applications where images are used to supply information to specialists who will choose suitable actions. An artificial neural classifier aids a fuzzy decision support system to deal with uncertainty and imprecision present in available information. Advantages of both techniques are exploited complementarily. As an example, this method was applied in automatic focus checking and adjustment in video monitor manufacturing. Copyright © 2005 IFAC.

Video target tracking by using competitive neural networks

A target tracking algorithm able to identify the position and to pursuit moving targets in video digital sequences is proposed in this paper. The proposed approach aims to track moving targets inside the vision field of a digital camera. The position and trajectory of the target are identified by using a neural network presenting competitive learning technique. The winning neuron is trained to approximate to the target and, then, pursuit it. A digital camera provides a sequence of images and the algorithm process those frames in real time tracking the moving target. The algorithm is performed both with black and white and multi-colored images to simulate real world situations. Results show the effectiveness of the proposed algorithm, since the neurons tracked the moving targets even if there is no pre-processing image analysis. Single and multiple moving targets are followed in real time.