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)

Cebus cf. apella exhibits rapid acquisition of complex stimulus relations and emergent performance by exclusion

A "second generation" matching-to-sample procedure that minimizes past sources of artifacts involves (1) successive discrimination between sample stimuli, (2) stimulus displays ranging from four to 16 comparisons, (3) variable stimulus locations to avoid unwanted stimulus-location control, and (4) high accuracy levels (e.g., 90% correct on a 16-choice task in which chance accuracy is 6%). Examples of behavioral engineering with experienced capuchin monkeys included four-choice matching problems with video images of monkeys with substantially above-chance matching in a single session and 90% matching within six sessions. Exclusion performance was demonstrated by interspersing non-identical sample-comparison pairs within a baseline of a nine-comparison identity-matching-to-sample procedure with pictures as stimuli. The test for exclusion presented the newly "mapped" stimulus in a situation in which exclusion was not possible. Degradation of matching between physically non-identical forms occurred while baseline identity accuracy was sustained at high levels, thus confirming that Cebus cf. apella is capable of exclusion. Additionally, exclusion performance when baseline matching relations involved non-identical stimuli was shown.

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

Capillary break-up rheometry of low-viscosity elastic fluids

We investigate the dynamics of the capillary thinning and break-up process for low viscosity elastic fluids such as dilute polymer solutions. Standard measurements of the evolution of the midpoint diameter of the necking fluid filament are augmented by high speed digital video images of the break up dynamics. We show that the successful operation of a capillary thinning device is governed by three important time scales (which characterize the relative importance of inertial, viscous and elastic processes), and also by two important length scales (which specify the initial sample size and the total stretch imposed on the sample). By optimizing the ranges of these geometric parameters, we are able to measure characteristic time scales for tensile stress growth as small as 1 millisecond for a number of model dilute and semi-dilute solutions of polyethylene oxide (PEO) in water and glycerol. If the final aspect ratio of the sample is too small, or the total axial stretch is too great, measurements are limited, respectively, by inertial oscillations of the liquid bridge or by the development of the well-known beads-on-a-string morphology which disrupt the formation of a uniform necking filament. By considering the magnitudes of the natural time scales associated with viscous flow, elastic stress growth and inertial oscillations it is possible to construct an operability diagram characterizing successful operation of a capillary break-up extensional rheometer. For Newtonian fluids, viscosities greater than approximately 70 mPas are required; however for dilute solutions of high molecular weight polymer, the minimum Viscosity is substantially lower due to the additional elastic stresses arising from molecular extension. For PEO of molecular weight 2.10(6) g/mol, it is possible to measure relaxation times of order 1 ms in dilute polymer solutions with zero-shear-rate viscosities on the order of 2-10 mPas.

Realtime telemedicine

Telemedicine conducted via prerecorded interaction is more convenient than that using realtime interaction. On the other hand, a realtime consultation allows an immediate result to be obtained and there is likely to be a strong educational component for the remote practitioner. The use of the telephone is under-rated in telemedicine. Telephones have been used in outpatient follow-up, mental health, help lines and support groups. Telephones (fixed and mobile) have also been used for data transfer (e.g. for transmission of electrocardiograms). Realtime transfer of still images has been used in telepathology for many years, and more recently for rapid assessment of injuries. Realtime transfer of video images has been widely explored, perhaps most successfully in telepsychiatry. Some realtime telemedicine applications have been taken up with enthusiasm, even if formal evidence of cost-effectiveness may be lacking. Teleradiology and telepsychiatry are two examples where widespread adoption is beginning to occur. Other forms of realtime telemedicine represent 'niche' applications. That is, they appear to be both successful and sustainable in the centres where they were pioneered, but have not been adopted elsewhere. Teledialysis and teleoncology are examples of this type. The patchy diffusion of telemedicine is something that is not yet well understood.

An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

Development of a real time Image analysis system for traffic monitoring applications.

Image processing offers unparalleled potential for traffic monitoring and control. For many years engineers have attempted to perfect the art of automatic data abstraction from sequences of video images. This paper outlines a research project undertaken at Napier University by the authors in the field of image processing for automatic traffic analysis. A software based system implementing TRIP algorithms to count cars and measure vehicle speed has been developed by members of the Transport Engineering Research Unit (TERU) at the University. The TRIP algorithm has been ported and evaluated on an IBM PC platform with a view to hardware implementation of the pre-processing routines required for vehicle detection. Results show that a software based traffic counting system is realisable for single window processing. Due to the high volume of data required to be processed for full frames or multiple lanes, system operations in real time are limited. Therefore specific hardware is required to be designed. The paper outlines a hardware design for implementation of inter-frame and background differencing, background updating and shadow removal techniques. Preliminary results showing the processing time and counting accuracy for the routines implemented in software are presented and a real time hardware pre-processing architecture is described.

Marine litter in the upper São Vicente submarine canyon (SW Portugal): abundance, distribution, composition and fauna interactions

Marine litter has become a worldwide environmental problem, tainting all ocean habitats. The abundance, distribution and composition of litter and its interactions with fauna were evaluated in the upper S. Vicente canyon using video images from 3 remote operated vehicle exploratory dives. Litter was present in all dives and the abundance was as high as 3.31 items100m(-1). Mean abundance of litter over rock bottom was higher than on soft substrate. Mean litter abundance was slightly higher than reported for other canyons on the Portuguese margin, but lower in comparison to more urbanized coastal areas of the world. Lost fishing gear was the prevalent type of litter, indicating that the majority of litter originates from maritime sources, mainly fishing activity. Physical contact with sessile fauna and entanglement of specimens were the major impacts of lost fishing gear. Based on the importance of this region for the local fishermen, litter abundance is expected to increase.

Deep learning models for the automatic analysis of volleyball plays

Collecting and analysing data is an important element in any field of human activity and research. Even in sports, collecting and analyzing statistical data is attracting a growing interest. Some exemplar use cases are: improvement of technical/tactical aspects for team coaches, definition of game strategies based on the opposite team play or evaluation of the performance of players. Other advantages are related to taking more precise and impartial judgment in referee decisions: a wrong decision can change the outcomes of important matches. Finally, it can be useful to provide better representations and graphic effects that make the game more engaging for the audience during the match. Nowadays it is possible to delegate this type of task to automatic software systems that can use cameras or even hardware sensors to collect images or data and process them. One of the most efficient methods to collect data is to process the video images of the sporting event through mixed techniques concerning machine learning applied to computer vision. As in other domains in which computer vision can be applied, the main tasks in sports are related to object detection, player tracking, and to the pose estimation of athletes. The goal of the present thesis is to apply different models of CNNs to analyze volleyball matches. Starting from video frames of a volleyball match, we reproduce a bird's eye view of the playing court where all the players are projected, reporting also for each player the type of action she/he is performing.

Modeling camera orientation and 3D structure from a sequence of images taken by a perambulating commercial video camera

In this paper we report the degree of reliability of image sequences taken by off-the-shelf TV cameras for modeling camera rotation and reconstructing 3D structure using computer vision techniques. This is done in spite of the fact that computer vision systems usually use imaging devices that are specifically designed for the human vision. Our scenario consists of a static scene and a mobile camera moving through the scene. The scene is any long axial building dominated by features along the three principal orientations and with at least one wall containing prominent repetitive planar features such as doors, windows bricks etc. The camera is an ordinary commercial camcorder moving along the axial axis of the scene and is allowed to rotate freely within the range +/- 10 degrees in all directions. This makes it possible that the camera be held by a walking unprofessional cameraman with normal gait, or to be mounted on a mobile robot. The system has been tested successfully on sequence of images of a variety of structured, but fairly cluttered scenes taken by different walking cameramen. The potential application areas of the system include medicine, robotics and photogrammetry.

Characters Extraction for Traffic Sign Destination boards in video and still images

Traffic Control Signs or destination boards on roadways offer significant information for drivers. Regulation signs tell something like your speed, turns, etc; Warning signs warn drivers of conditions ahead to help them avoid accidents; Destination signs show distances and directions to various locations; Service signs display location of hospitals, gas and rest areas etc. Because the signs are so important and there is always a certain distance from them to drivers, to let the drivers get information clearly and easily even in bad weather or other situations. The idea is to develop software which can collect useful information from a special camera which is mounted in the front of a moving car to extract the important information and finally show it to the drivers. For example, when a frame contains on a destination drive sign board it will be text something like "Linkoping 50",so the software should extract every character of "Linkoping 50", compare them with the already known character data in the database. if there is extracted character match "k" in the database then output the destination name and show to the driver. In this project C++ will be used to write the code for this software.